This position leads the medical strategy for assigned oncology indication(s)/asset(s), driving launch excellence, shaping evidence generation, and building confidence in our science across the globe.

Acting as the key bridge between R&D and Commercial, this role steers the Global Medical Plan, orchestrates global launch readiness, and ensures that every decision is grounded in robust data and patient impact.

Ready to influence how new oncology medicines are understood, adopted, and scaled across diverse healthcare systems?

Accountabilities

• Provide strategic medical leadership for assigned indication(s)/asset(s), owning the Global Medical Plan and leading launch strategy from early planning through post-launch optimisation.

• Set clear strategic direction, prioritise initiatives, and make evidence-based trade-offs to maximise patient outcomes and business impact, adapting plans in response to external dynamics and performance against launch KPIs.

• Define, track, and interpret medical Key Performance Indicators to assess strategy impact, identify progress, and diagnose barriers to launch success.

• Represent Global Medical on key cross-functional forums such as the Integrated Business Team and Global Product Team, shaping commercial strategy, informing R&D development and lifecycle planning, and ensuring Medical input into clinical development and commercialisation strategies.

• Lead Medical Integrated Teams to align global, regional, and country medical teams around launch strategy and execution, acting as a medical decision-maker and ambassador in market engagements.

• Influence clinical development by identifying registrational evidence gaps, companion study needs, and Target Product Profile implications, ensuring Medical perspectives shape Tumor Strategic Plans and Business Strategy Plans.

• Strengthen global medical capabilities through effective delegation, coaching, empowerment, and mentorship, building high-performing teams focused on launch excellence.

• Lead global and regional evidence gap analyses to define critical clinical, real-world, and mechanistic evidence needs, and develop integrated evidence plans across clinical, diagnostic, digital, and real-world sources.

• Shape the scientific and strategic design of AZ-sponsorised interventional Medical Affairs studies, conceptualise real-world evidence studies with partners, and oversee governance, milestones, and resources to deliver to the highest scientific, ethical, and compliance standards.

• Own the Global Publications Plan from Phase 3 ID onwards in partnership with publications teams, ensuring compelling, credible scientific communications and appropriate review of local/regional medical studies and Externally Sponsored Research.

• Embed innovative approaches to evidence generation aligned with the MARS vision, leveraging cancer networks, novel study designs, and data-driven insights.

• Own and lead the scientific narrative from pre-Phase 3 ID onwards, ensuring consistency across evidence, publications, congresses, and education while driving an Integrated Confidence Plan executed by Centres of Excellence.

• Define global medical education priorities, identify key audiences and learning objectives, guide delivery formats (digital, hybrid, in-person), and ensure scientific rigor in all educational activities.

• Lead the external engagement strategy for indication(s)/asset(s), including KEEs, societies, health systems, and global organisations; gather insights that shape scientific practice and actively influence external experts to advance health outcomes and accelerate guideline adoption.

• Lead congress strategy end-to-end: drive pre-congress planning (abstracts, presentations, training), guide on-site scientific presence, and oversee post-congress insight synthesis, dissemination, and follow-up actions.

Essential Skills/Experience

• Advanced degree required (MD, PhD, PharmD, in any related field)

• At least three years of experience within the pharmaceutical or biotech industry, ideally at the country, Region and global level.

• Demonstrated success in leading evidence generation strategies, Medical Plans, publications, or scientific communication programs.

• Proven ability to influence senior stakeholders across Commercial, R&D, and Medical Affairs.

• Experience engaging external experts and scientific communities.

Desirable Skills/Experience

• Previous global Medical Affairs leadership experience in oncology.

• Experience leading cross-functional teams in highly complex, multi-indication environments.

• Experience navigating launch environments, new MoAs, new CDx, complex biomarker landscapes, or challenging safety profiles (aligning to GMAL complexity criteria).

Benefits

AstraZeneca offers an environment where scientific curiosity meets real-world impact: a global biopharmaceutical company tackling serious disease while constantly searching for new ways to solve complex healthcare and sustainability challenges.

Teams reflect the diversity of the communities we serve; different perspectives are encouraged, collaboration is expected, and questioning minds are supported to push boundaries.

With strong investment in learning, data and digital innovation, and cross-functional partnerships inside and outside the organisation, people are empowered to take smart risks, learn fast from experience, and contribute directly to life-changing medicines for patients worldwide.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.

We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.

We follow all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

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The Director, Publications Strategy will support the TA medical directors to ensure successful development and implementation of the publication plans. They will review and interpret product data from preclinical, clinical development, statistics, and health economics departments within Bayer and external investigators to determine appropriate publications for inclusion in tactical publications plans.

Key responsibilities include liaising with global publications leads, communicating global publications initiatives to the US product teams, and ensuring US publications initiatives are aligned with the global publication strategy and plan. The Director will also review and edit congress abstracts, oral and poster presentations, primary and secondary manuscripts, and slide presentations developed by vendors and external investigators to ensure publications are high-quality and adhere to Good Publication Practices and Bayer's Publication Policy and SOP.

Additional responsibilities include serving as the point person for all units within US and global medical affairs that contribute to or are affected by publication development, hosting internal and external US-specific publication-related team meetings, and ensuring that all vendors comply with Bayer operational guidelines.

The ideal candidate will possess an advanced degree in a scientific discipline, proven ability to interpret scientific and clinical trial data, and strong scientific writing and editing skills. They should also have knowledge of Good Publication Practices and the ability to work effectively within these guidelines.

Preferred qualifications include minimum 4 years' experience in the development and execution of strategic publications plans within the pharmaceutical or biotech industry, antithrombotic or vascular neurology experience, and experience working with a publications management tool.

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Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviours, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Responsibilities

• Build and deploy multi-agent systems for agentic reasoning validation
• Develop pipelines to detect errors and scale human judgment
• Combine classical ML, LLMs, and multi-agent techniques for reliability
• Lead research into agent failure modes and ship fixes
• Use AI tools to speed prototyping and iteration
• Build data-driven evaluations and deploy rapid improvements
• Integrate systems into Scale's platform

Ideal Candidate

• PhD or MSc in Computer Science, Mathematics, Statistics, or related field
• 3+ years shipping scaled production ML systems
• Demonstrated real-world impact
• Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
• Deep expertise in agentic LLMs and multi-agent systems
• Strong software engineering and microservices (AWS/GCP)
• Rapid, data-driven iteration
• Proficiency using AI tools to accelerate work
• Strong research depth with practical bias
• Excellent cross-functional communication

Nice to Have

• Experience prototyping agent evaluation/reliability systems
• Human-in-the-loop or annotation pipeline work
• Open-source contributions in agents, evaluation, or alignment
• Publications on agent reliability (NeurIPS, ICML, ICLR)

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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Your responsibilities will include serving as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings.

You will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.

You will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

You will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.

You will act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

You will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.

You will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

You will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.

You will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

You will represent CoreWeave at conferences and industry events, with occasional travel as required.

To be successful in this role, you will need to have a B.S. in Computer Science or a related technical discipline, or equivalent experience.

You will also need to have 7+ years of proven experience as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure, focusing on building distributed systems or HPC/cloud services, with an expertise focused on scalable Kubernetes solutions.

You will need to be fluent in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.

You will need to have a proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences.

You will need to be familiar with NVIDIA GPUs typically used in AI/ML applications and associated technologies such as Infiniband and NVIDIA Collective Communications Library (NCCL).

You will need to have experience with running large-scale Artificial Intelligence/Machine Learning (AI/ML) training and inference workloads on technologies such as Slurm and Kubernetes.

Preferred qualifications include code contributions to open-source inference frameworks, experience with scripting and automation related to Kubernetes clusters and workloads, experience with building solutions across multi-cloud environments, and client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures.

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You will:

• Build synthetic data pipelines to generate enterprise environments to use for RL post-training
• Create agents to convert traces from production into actionable insights to use to improve agents
• Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms
• Train state-of-the-art models, developed both internally and from the community, to deploy to our enterprise customers

Ideally, you'd have:

• 3+ years of building with LLMs in a production environment
• Clear experiences with constructing high-quality data to use to improve an LLM/Agent
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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This role is ideal for someone who thrives at the intersection of research and systems engineering: a builder who understands both the math of optimization and the realities of distributed compute.

Responsibilities:

• Design and optimize distributed training infrastructure for large-scale LLMs, focusing on performance, stability, and reproducibility across multi-GPU and multi-node setups.
• Implement and evaluate low-precision numerics (for example, BF16, MXFP8, NVFP4) to improve efficiency without sacrificing model quality.
• Develop kernels and communication primitives that use hardware-level support for mixed and low-precision arithmetic.
• Collaborate with research teams to co-design model architectures and training recipes that align with emerging numeric formats and stability constraints.
• Prototype and benchmark scaling strategies such as data, tensor, and pipeline parallelism that integrate precision-adaptive computation and quantized communication.
• Contribute to the design of our internal orchestration and monitoring systems to ensure that thousands of distributed experiments can run efficiently and reproducibly.
• Publish and share learnings through internal documentation, open-source libraries, or technical reports that advance the field of scalable AI infrastructure.

Skills and Qualifications:

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.
• Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.
• Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases in areas such as floating-point numerics, low-precision arithmetic, and distributed systems.

Preferred qualifications , we encourage you to apply if you meet some but not all of these:

• Familiarity with distributed frameworks such as PyTorch/XLA, DeepSpeed, Megatron-LM.
• Experience implementing FP8, INT8, or block-floating point (MX) formats and understanding their numerical trade-offs.
• Prior contributions to open-source deep learning infrastructure such as PyTorch, DeepSpeed, or XLA.
• Publications, patents, or projects related to numerical optimization, communication-efficient training, or systems for large models.
• Experience training and supporting large-scale AI models.
• Track record of improving research productivity through infrastructure design or process improvements.

Logistics:

• Location: This role is based in San Francisco, California.
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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We're looking for a Senior Machine Learning Engineer to join our Monetization team. As a key member of the team, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

Key responsibilities include:

• Building cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partnering closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search)
• Using data-driven methods and leveraging the unique properties of our data to improve candidate retrieval
• Working in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems

Requirements:

• 2+ years of industry experience applying machine learning methods
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies
• Practical knowledge of large-scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Nice to have:

• M.S. or PhD in Machine Learning or related areas
• Publications at top ML conferences
• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
• Expertise in scalable real-time systems that process stream data
• Passion for applied ML and the Pinterest product
• Background in computational advertising

Relocation Statement:

This position is not eligible for relocation assistance.

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Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements. Lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

Drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise. Act as a virtual member of CoreWeave's Storage product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

Offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture. Conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

Stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders. Lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

Represent CoreWeave at conferences and industry events, with occasional travel as required.

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Senior Psychologist

Job Description

We are seeking a Senior Psychologist to join the Responsible Development & Innovation team (ReDI) at Google DeepMind. The candidate should have relevant prior industry experience, a strong general understanding of core psychological principles and the ability to leverage internal and external expertise and research experience in AI-related areas (e.g., cognitive, behavioural).

Responsibilities

As a Senior Psychologist within the Ethics Foresight team, you will be pivotal in ensuring our advanced AI models interact with people, in healthy and developmentally appropriate ways, consistent with Google DeepMind's values. You will use your intellectual agility and deep expertise in psychology to proactively identify and address potential ethical and well-being implications of our AI technologies. You will be engaging with senior stakeholders to champion our efforts. This role demands someone capable of quickly grasping and contributing to diverse topics while possessing a strong foundational understanding of psychological principles, especially as they relate to human-computer interaction.

Key Responsibilities

• General AI Psychology Guidelines: Develop practical guidelines and frameworks informed by general psychological principles (e.g., cognitive biases, well-being, mental health, developmental) and empirical data to ensure that AI models interact in ways that promote positive outcomes and mitigate potential psychological harms.
• Support Implementation: Convert these frameworks into artefacts that include training datasets and evaluation protocol.

Collaborate with model development teams to advise on and facilitate the creation and implementation of evaluation frameworks, defining key metrics, tracking protocols, and criteria for significant results.

• Emerging Trends: Stay informed about the latest research and emerging trends in psychology, and the evolving landscape of AI and its potential impact on users.
• Risk Identification and Analysis: Proactively identify and research potential psychological risks and ethical considerations arising from interactions between advanced AI and users, drawing upon your expertise psychology, and related fields.
• Interdisciplinary Collaboration: Work closely with AI researchers, engineers, product managers, across Google DeepMind to integrate psychological insights into the AI development lifecycle.
• Literature Review and Expert Consultation: Conduct thorough reviews of relevant academic literature in psychology, education and technology, human-computer interaction, and AI ethics.

Engage with internal and external experts to gather diverse perspectives and inform guideline development.

Requirements

In order to set you up for success as a Senior Psychologist for Model Policy Research at Google DeepMind, we look for the following skills and experience:

• A PhD in Psychology (Clinical, Developmental, Social, Cognitive), Education and Technology, or related fields.
• Significant research experience and publications on Human-AI interaction in one or more of the following areas: affective science, cognitive science, child development, adolescent psychology, attachment theory, social-emotional learning, or other relevant areas of applied psychology.
• Extensive prior experience working in a leading industry position.
• A strong understanding of ethical principles and considerations relevant to psychological research and the application of psychological principles in technology.
• Demonstrated ability to learn quickly and contribute effectively to new and varied subjects outside of core expertise.
• Excellent research, analytical, and problem-solving skills, with the ability to critically evaluate complex information.
• Strong written and verbal communication skills, with the ability to explain complex psychological concepts clearly and concisely to both technical and non-technical audiences.
• Ability to collaborate effectively within interdisciplinary teams and contribute to a fast-paced environment.
• A proactive and independent approach to identifying and addressing potential challenges and exploring novel research questions.
• Experience with ethical considerations in technology development and familiarity with AI concepts and technologies.
• Experience in applied research settings or translating academic knowledge into practical guidelines or applications.
• Experience in engaging with cross-functional teams.
• Technical proficiency and an in-depth understanding of the end-to-end AI development process and model lifecycles.

Salary

The US base salary range for this full-time position is between $174,000 - $258,000 + bonus + equity + benefits.

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Your primary responsibility will be to serve as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings.

You will collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.

You will lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

You will drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.

You will act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

You will offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.

You will conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.

You will stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.

You will lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

You will represent CoreWeave at conferences and industry events, with occasional travel as required.

To be successful in this role, you will need to have a proven track record of working as a Solutions Architect, engineer, researcher, or technical account manager in cloud infrastructure, focusing on building distributed systems or HPC/cloud services, with an expertise focused on scalable Kubernetes solutions.

You will also need to have fluency in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions.

In addition, you will need to have a proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences.

Preferred qualifications include code contributions to open-source inference frameworks, experience with scripting and automation related to Kubernetes clusters and workloads, experience with building solutions across multi-cloud environments, and client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures.

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Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements. Lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.

Drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise. Act as a virtual member of CoreWeave's Kubernetes product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.

Offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture. Conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimisation and suggesting suitable solutions.

Stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders. Lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.

Represent CoreWeave at conferences and industry events, with occasional travel as required.

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You will also be an integral part of achieving industry-leading end-to-end performance benchmarking publications: If MLPerf (Training & Inference), Working closely with NVIDIA (Megatron-LM, TensorRT-LLM & DGX cloud) and the open-source community (llm-d, vLLM and all popular ML frameworks) speak to you, come help us demonstrate CoreWeave's performance reliability leadership in the field.

Responsibilities

• Strategy & Leadership - Define the multi-year benchmarking strategy and roadmap; prioritize models/workloads (LLMs, diffusion, vision, speech) and hardware tiers. Build, lead, and mentor a high-performing team of performance engineers and data analysts. Establish governance for claims: documented methodologies, versioning, reproducibility, and audit trails.

• Perf Ownership - Lead end-to-end MLPerf Inference and Training submissions: workload selection, cluster planning, runbooks, audits, and result publication. Coordinate optimization tracks with NVIDIA (CUDA, cuDNN, TensorRT/TensorRT-LLM, Triton, NCCL) to hit competitive results; drive upstream fixes where needed.

• Internal Latency & Throughput Benchmarks - Design a Kubernetes-native, repeatable benchmarking service that exercises CoreWeave stacks across SUNK (Slurm on Kubernetes), Kueue, and Kubeflow pipelines. Measure and report p50/p95/p99 latency, jitter, tokens/s, time-to-first-token, cold-start/warm-start, and cost-per-token/request across models, precisions (BF16/FP8/FP4), batch sizes, and GPU types. Maintain a corpus of representative scenarios (streaming, batch, multi-tenant) and data sets; automate comparisons across software releases and hardware generations.

• Tooling & Automation - Build CI/CD pipelines and K8s controllers/operators to schedule benchmarks at scale; integrate with observability stacks (Prometheus, Grafana, OpenTelemetry) and results warehouses. Implement supply-chain integrity for benchmark artifacts (SBOMs, Cosign signatures).

• Cross-functional & Community - Partner with NVIDIA, key ISVs, and OSS projects (vLLM, Triton, KServe, PyTorch/DeepSpeed, ONNX Runtime) to co-develop optimizations and upstream improvements. Support Sales/SEs with authoritative numbers for RFPs and competitive evaluations; brief analysts and press with rigorous, defensible data.

Requirements

• 10+ years building distributed systems or HPC/cloud services, with deep expertise on large-scale ML training or similar high-performance workloads.

• Proven track record of architecting or building planet-scale data systems (e.g., telemetry platforms, observability stacks, cloud data warehouses, large-scale OLAP engines).

• Deep understanding of GPU performance (CUDA, NCCL, RDMA, NVLink/PCIe, memory bandwidth), model-server stacks (Triton, vLLM, TensorRT-LLM, TorchServe), and distributed training frameworks (PyTorch FSDP/DeepSpeed/Megatron-LM).

• Proficient with Kubernetes and ML control planes; familiarity with SUNK, Kueue, and Kubeflow in production environments.

• Excellent communicator able to interface with executives, customers, auditors, and OSS communities.

Nice to have

• Experience with time-series databases, log-structured merge trees (LSM), or custom storage engine development.

• Experience running MLPerf submissions (Inference and/or Training) or equivalent audited benchmarks at scale.

• Contributions to MLPerf, Triton, vLLM, PyTorch, KServe, or similar OSS projects.

• Experience benchmarking multi-region fleets and large clusters (thousands of GPUs).

• Publications/talks on ML performance, latency engineering, or large-scale benchmarking methodology.

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The Market Intelligence team operates at the intersection of technical infrastructure, product, data center development, and the global supply chain. The team provides forward-looking insights on markets, competitors, suppliers, customers, and macro forces to inform CoreWeave's infrastructure investments, product roadmaps, and supply chain strategies across GPUs, networking, power, cooling, and site development.

Key responsibilities include:

• Demonstrated leadership experience building and leading Market Intelligence or strategic analytics teams in AI, hyperscale cloud, or high-growth technology environments
• Proven track record delivering measurable value and cost savings across hyperscale or large-scale infrastructure supply chains
• Deep experience conducting competitive intelligence across neocloud and hyperscale cloud providers, including data center and supply chain strategies
• Strong expertise in supplier ecosystem analysis, including supplier financial health, capacity, pricing, lead times, and technology roadmaps
• Experience analyzing regulatory, public policy, utility, and geopolitical factors impacting global infrastructure supply chains and data center operations
• Advanced capability in strategic analytics and modeling, including demand forecasting, inventory optimization, and commodity procurement models
• Demonstrated ability to influence executive decision-making through data-driven insights and strategic recommendations

Preferred qualifications include:

• Recognized industry expertise through publications, conference speaking, or professional/academic recognition in operations research, supply chain, or market analysis
• Experience supporting both infrastructure strategy and customer acquisition or go-to-market planning
• Exposure to global site development, utilities, or large-scale data center construction ecosystems

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

All of our AI Tutor roles potentially involve gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions,tasks with which candidates must be comfortable.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modelling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialisation in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organisational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgement even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modelling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

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Your primary responsibilities will include designing and driving projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest. You'll collaborate with other engineering teams to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest.

You'll also mentor junior engineers on the Responsible AI team and across the company on the R-AI space, and work with the team and senior leaders at the company to define and drive technical strategy in this area.

To be successful in this role, you'll need extensive, real-world experience applying advanced ML methods to production systems, with a strong track record in responsible technology spanning fairness, ethics, and broader societal considerations. You'll also need deep familiarity with cutting-edge ML architectures and their applications in large-scale Search and Recommender Systems.

In addition, you'll need proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact. You'll also need 4+ years working experience in the engineering teams that build large-scale ML-driven user-facing products, and 1+ years experience leading cross-team engineering efforts.

Nice to have: publications at top ML conferences, experience using AI coding assistants, familiarity with LLM-powered productivity tools, and expertise in scalable real-time systems that process stream data.

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As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

Key Responsibilities:

• Own the technical vision and architecture for platform security across Anduril's product ecosystem
• Design cryptographic systems, protocols, and key management architectures for autonomous and robotic platforms operating in contested and disconnected environments
• Lead the design of hardware root-of-trust architectures integrating TPMs, TEEs, HSMs, and secure boot across diverse embedded platforms
• Drive the strategy for promoting business-line security implementations into shared, composable platform services
• Serve as the senior technical authority for security architecture reviews across the organization, providing definitive guidance on cryptographic design, protocol security, and system hardening
• Define security patterns, reference architectures, and engineering standards that enable teams across Anduril to build securely and independently
• Mentor and develop senior engineers on the team, raising the bar for security engineering across the organization
• Represent Anduril's security engineering capabilities to customers, partners, and auditors when deep technical credibility is required
• Evaluate emerging threats, cryptographic standards, and security technologies, driving adoption where they strengthen the platform

Required Qualifications:

• 12+ years of experience in software engineering, with significant depth in systems security and cryptography
• Expert-level knowledge of cryptographic protocol design, including key management architectures, certificate systems, and cryptographic agility
• Deep experience with hardware security: TPM, TEE, HSM, secure boot, and hardware root-of-trust design across multiple platform types
• Proficient in two or more of: C++, Rust, Go
• Experience designing security architectures for embedded, real-time, or robotic systems with constrained environments
• Track record of leading cross-organizational technical initiatives and driving architectural decisions that span multiple teams
• Strong ability to communicate complex security concepts to engineering leadership, product teams, and external stakeholders
• Experience performing and leading threat modeling, security architecture reviews, and cryptographic design reviews
• Eligible to obtain and maintain active U.S. Secret security clearance

Preferred Qualifications:

• Experience with post-quantum cryptography, distributed key generation (DKG), or threshold cryptographic schemes
• Background in defense, aerospace, or autonomous systems with exposure to FIPS 140, Common Criteria, or NSA CSfC requirements
• Experience designing secure communication protocols for autonomous platforms or mesh networks
• Deep knowledge of Linux kernel security, mandatory access controls (SELinux/AppArmor), and OS hardening at scale
• Experience building and evolving platform security services consumed by dozens of teams
• Familiarity with compliance frameworks (STIGs, NIST 800-53, CMMC) and translating them into engineering controls that don't compromise developer velocity
• Publications, patents, or recognized contributions in cryptography or systems security
• Experience with Nix build systems and reproducible build pipelines for security-critical software

US Salary Range: $254,000-$336,000 USD

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create complex problems from advanced pure math topics to boost performance.

Key responsibilities include:

• Using proprietary software applications to provide input/labels on defined projects.
• Supporting and ensuring the delivery of high-quality curated data.
• Playing a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interacting with the technical staff to help improve the design of efficient annotation tools.
• Choosing problems from pure math subdomains that align with your expertise, focusing on areas like abstract algebra, real/complex analysis, topology, graph theory, and so on where you can confidently provide detailed solutions and evaluate model responses.

To succeed in this role, you'll need:

• A Master's or PhD in Mathematics with a specialization in a subdomain of pure mathematics, or a medal in an International Math Olympiad (IMO) or similar level math competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.

Preferred skills and experience include:

• Math PhD with a specialization in a subdomain of pure mathematics.
• Peer-reviewed pure math publications in well-regarded journals.
• Previous AI Tutoring experience and/or experience teaching college courses.

As a remote worker, you'll have the flexibility to set your own hours and determine the exact amount of time needed to complete deliverables. Compensation ranges from $45/hour to $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. Benefits vary based on employment type, location, and jurisdiction.

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modeling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialization in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modeling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

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Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

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The ideal candidate will have a strong background in computer science, robotics, machine learning, or a related field, and experience integrating agents into classical systems. They will also have a proven track record of novel application and experience including first-author publications, participation in peer-reviewed conferences, contribution to open-source projects, and demonstrated contribution to the ML and AI community.

In addition to your technical expertise, you will be a strong communicator and collaborator, able to work effectively with cross-functional teams to drive results. You will also be comfortable working in a fast-paced environment and adapting to changing priorities.

If you are a motivated and experienced engineer looking to join a dynamic team and contribute to cutting-edge technology, we encourage you to apply.

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The ideal candidate will have several years of experience working with enterprise, NaaS, or security technologies. They will have a passion for building NaaS products and want to solve the problems of performance, security, and reliability of the Internet.

Role Responsibilities:

• Owning the product vision for your area. Ensure that it aligns with the overall product and company vision.
• Representing the customer. Be the champion and voice of customers. Build meaningful, personal customer relationships. Bring the customer's voice into the creation process.
• Managing the roadmap. Make tough tactical prioritization decisions while helping the company think long-term. Build trust with stakeholders by maintaining an understandable, accurate roadmap.
• Authoring use cases and prioritizing requirements. Translate market observations and customer feedback into a prioritized product backlog.
• Collaborating across teams. We win or lose as a team. Product managers play a critical role in creating alignment between engineering teams and other stakeholders. A collaborative attitude is essential to the job.
• Measuring success. Own the measures used to define success for your product. Success measures must be defined at the inception of a product and tracked throughout its lifecycle. Make measures visible to all stakeholders and interpret them into actionable conclusions and new hypotheses.

Must-Have Skills:

• 5-10 years working as a Product Manager or Technical Product Manager shipping enterprise class software, or relevant experience
• Strong technical understanding of L3-L7 networking including routing protocols, common network architectures and secure connectivity within cloud environments (AWS, Azure, GCP)
• Experience working alongside multiple disciplines (ex. Design, engineering, support, sales) and decision makers to ship software
• Excellent customer facing skills (empathy, problem solving, clear and succinct communicator)
• Ability to work with common software and networking tools like Postman or curl to interact with RESTful Web APIs, Terraform for automated provisioning of cloud networking resources
• Experience with up-to-date AI tools (agents and IDEs) for vibecoding and prototyping

Nice-to-Have Skills:

• Experience with modern SASE or SSE solutions (either building or implementing)
• Experience with large-scale distributed systems and cloud-native architectures
• Active participation in industry conferences, publications, or open-source projects related to networking or security

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Key responsibilities include:

• Post-training/instruction tuning state-of-the-art LLMs, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini Models are safe, maximally helpful, and work for everyone
• Improve Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Design and maintain high-quality evaluation protocols to assess model behavior gaps and headroom related to safety and fairness
• Develop and execute experimental plans to address known gaps, or construct entirely new capabilities
• Drive innovation and enhance understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale

To succeed as a Research Scientist in the Gemini Safety team, we look for the following skills and experience:

• PhD in Computer Science, a related field, or equivalent practical experience
• Significant LLM post-training experience
• Experience in Reward modeling and Reinforcement Learning for LLMs Instruction tuning
• Experience with Long-range Reinforcement learning
• Experience in areas such as Safety, Fairness, and Alignment
• Track record of publications at NeurIPS, ICLR, ICML
• Experience taking research from concept to product
• Experience with collaborating or leading an applied research project
• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing
• Experience with JAX

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Senior Psychologist

Job Description

We are seeking a Senior Psychologist to join the Responsible Development & Innovation team (ReDI) at Google DeepMind. The candidate should have relevant prior industry experience, a strong general understanding of core psychological principles and the ability to leverage internal and external expertise and research experience in AI-related areas (e.g., cognitive, behavioural).

Responsibilities

As a Senior Psychologist within the Ethics Foresight team, you will be pivotal in ensuring our advanced AI models interact with people, in healthy and developmentally appropriate ways, consistent with Google DeepMind's values. You will use your intellectual agility and deep expertise in psychology to proactively identify and address potential ethical and well-being implications of our AI technologies. You will be engaging with senior stakeholders to champion our efforts. This role demands someone capable of quickly grasping and contributing to diverse topics while possessing a strong foundational understanding of psychological principles, especially as they relate to human-computer interaction.

Key Responsibilities

• General AI Psychology Guidelines: Develop practical guidelines and frameworks informed by general psychological principles (e.g., cognitive biases, well-being, mental health, developmental) and empirical data to ensure that AI models interact in ways that promote positive outcomes and mitigate potential psychological harms.
• Support Implementation: Convert these frameworks into artefacts that include training datasets and evaluation protocol.

Collaborate with model development teams to advise on and facilitate the creation and implementation of evaluation frameworks, defining key metrics, tracking protocols, and criteria for significant results.

• Emerging Trends: Stay informed about the latest research and emerging trends in psychology, and the evolving landscape of AI and its potential impact on users.
• Risk Identification and Analysis: Proactively identify and research potential psychological risks and ethical considerations arising from interactions between advanced AI and users, drawing upon your expertise psychology, and related fields.
• Interdisciplinary Collaboration: Work closely with AI researchers, engineers, product managers, across Google DeepMind to integrate psychological insights into the AI development lifecycle.
• Literature Review and Expert Consultation: Conduct thorough reviews of relevant academic literature in psychology, education and technology, human-computer interaction, and AI ethics.

Engage with internal and external experts to gather diverse perspectives and inform guideline development.

Requirements

In order to set you up for success as a Senior Psychologist for Model Policy Research at Google DeepMind, we look for the following skills and experience:

• A PhD in Psychology (Clinical, Developmental, Social, Cognitive), Education and Technology, or related fields.
• Significant research experience and publications on Human-AI interaction in one or more of the following areas: affective science, cognitive science, child development, adolescent psychology, attachment theory, social-emotional learning, or other relevant areas of applied psychology.
• Extensive prior experience working in a leading industry position.
• A strong understanding of ethical principles and considerations relevant to psychological research and the application of psychological principles in technology.
• Demonstrated ability to learn quickly and contribute effectively to new and varied subjects outside of core expertise.
• Excellent research, analytical, and problem-solving skills, with the ability to critically evaluate complex information.
• Strong written and verbal communication skills, with the ability to explain complex psychological concepts clearly and concisely to both technical and non-technical audiences.
• Ability to collaborate effectively within interdisciplinary teams and contribute to a fast-paced environment.
• A proactive and independent approach to identifying and addressing potential challenges and exploring novel research questions.
• Experience with ethical considerations in technology development and familiarity with AI concepts and technologies.
• Experience in applied research settings or translating academic knowledge into practical guidelines or applications.
• Experience in engaging with cross-functional teams.
• Technical proficiency and an in-depth understanding of the end-to-end AI development process and model lifecycles.

Salary

The US base salary range for this full-time position is between $174,000 - $258,000 + bonus + equity + benefits.

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging applied math problems to boost performance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from applied math domains that align with your expertise, focusing on areas such as probability, statistics, numerical analysis, optimization, operations research, dynamical systems, data modeling, and related fields where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Mathematics with a specialization in a subdomain of applied mathematics (there is a separate position for pure math) or (b) a medal in an International Math Olympiad (IMO) or similar level math competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• Math PhD with a specialization in a subdomain of applied mathematics.
• Peer-reviewed applied math publications in well-regarded journals.
• Previous AI Tutoring experience and/or experience teaching college courses.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

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Your deep domain knowledge will guide the selection and rigorous solving of complex problems in quantitative crypto strategies , including on-chain analysis, DeFi protocols, perpetual futures & derivatives trading, cross-exchange arbitrage, market microstructure in fragmented venues, MEV-aware execution, machine learning for crypto alpha signals, and portfolio/risk management in high-volatility 24/7 markets.

This role demands sharp quantitative thinking, quick adaptation to evolving instructions, and the ability to deliver precise, technically robust critiques and solutions in a dynamic environment.

Responsibilities:

• Utilize proprietary software to deliver accurate labels, rankings, critiques, and in-depth solutions on assigned projects
• Consistently produce high-quality, curated data adhering to rigorous technical and domain standards
• Partner with engineers and researchers to iterate on new training tasks, evaluation frameworks, and crypto-specific benchmarks
• Offer actionable feedback to enhance the efficiency, accuracy, and usability of annotation and data-collection interfaces
• Identify and solve challenging problems from crypto & digital asset domains where you have strong expertise , examples include:

• On-chain metrics analysis and wallet/flow clustering for alpha generation
• DeFi yield farming, liquidity provision, and impermanent loss modeling
• Cross-exchange / CEX-DEX arbitrage and triangular opportunities
• Perpetual futures funding rate strategies and basis trading
• Market microstructure in crypto order books (fragmented liquidity, MEV, sandwich attacks)
• Machine learning models for price prediction, sentiment from social/on-chain, volatility forecasting
• Tokenomics evaluation, airdrop/IDO quantitative assessment, and risk premia in altcoins
• Portfolio optimization and risk management in 24/7 high-volatility environments

• Provide rigorous critiques of model outputs, alternative quantitative approaches, mathematical derivations, code snippets, and step-by-step crypto reasoning
• Efficiently interpret, analyze, and complete tasks based on detailed (and evolving) guidelines

Basic Qualifications:

• Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Computer Science (with crypto/blockchain focus), Statistics, Applied Mathematics, Economics (quantitative), Physics, Operations Research, Data Science, or closely related field or equivalent professional experience as a quantitative crypto trader, systematic strategist, or on-chain analyst
• Superior written and verbal English communication (technical papers, explanatory breakdowns, professional correspondence)
• Extensive hands-on familiarity with crypto data sources and tools (CoinGecko, CoinMarketCap, Dune Analytics, Glassnode, Nansen, Chainalysis, Messari, DefiLlama, The Graph, blockchain explorers, CEX APIs, on-chain datasets, etc.)
• Outstanding analytical skills, attention to detail, and sound judgment under partial information

Preferred Skills and Experience:

• Professional experience in quantitative crypto trading, systematic strategies, or on-chain research at a crypto hedge fund, prop desk, market-making firm, DeFi protocol, or digital asset investment firm
• Publications or public analyses in crypto quant topics (e.g., journals, conferences, reputable blogs, GitHub repos with notable traction)
• Teaching, mentoring, or content-creation experience in crypto/quant finance (university, bootcamps, Twitter threads, newsletters)
• Proficiency in Python for crypto analysis (pandas, NumPy, ccxt, web3.py, etherscan APIs, polars, scikit-learn, PyTorch/TensorFlow for ML models, etc.) and/or Rust/Solidity familiarity
• Experience with backtesting crypto strategies, handling tick-level or on-chain data, managing API rate limits, and dealing with 24/7 market quirks
• Knowledge of MEV, flash loans, oracle manipulation risks, liquidation cascades, or other crypto-native phenomena
• CFA, FRM, CQF, or blockchain-specific certifications (e.g., Certified Blockchain Expert)
• Prior involvement with LLMs, reinforcement learning, or AI evaluation in financial/crypto contexts (strong plus)

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: $25/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications.

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This is a highly operational, systems-driven role that also demands creativity, intuition, and deep curiosity about the AI research ecosystem. You will work closely with founders, research leaders, and hiring managers to translate ambitious research goals into exceptional hires.

Responsibilities:

• Design, build, and continuously improve recruiting and sourcing systems, processes, and tooling with an emphasis on rigor, accuracy, and scalability
• Proactively source researchers and engineers from top universities, AI labs, and leading technology companies across ML, robotics, computer vision, and related fields
• Maintain exceptionally high-quality candidate data, pipelines, and documentation across ATS and internal tracking systems
• Develop creative sourcing strategies using publications, citations, open-source work, conference participation, academic networks, and referrals
• Partner closely with research and engineering leaders to deeply understand technical needs, evolving skill requirements, and long-term talent strategy
• Own candidate experience end-to-end, ensuring thoughtful, timely, and highly professional communication
• Analyze recruiting metrics and pipeline data to identify gaps, improve efficiency, and inform hiring decisions
• Support interview coordination and hiring operations as needed to keep processes running smoothly and predictably

Key Qualifications:

• 3+ years of experience in technical recruiting or sourcing, with a strong focus on AI, ML, robotics, or adjacent deep-tech domains
• Demonstrated ability to build and maintain highly organized recruiting systems and processes
• Strong data discipline: comfortable working with pipelines, metrics, and structured tracking to drive decisions
• Solid understanding of the AI research landscape, including top universities, labs, conferences, and industry research teams
• Experience sourcing passive, highly competitive candidates
• Excellent written and verbal communication skills
• Ability to operate effectively in fast-moving, ambiguous environments

Preferred Qualifications:

• Experience in one or more of the following is a strong plus:

  • Recruiting or sourcing for research-heavy organizations or frontier AI labs
  • Familiarity with academic research signals (publications, citations, arXiv, conferences such as NeurIPS, ICML, ICLR, CVPR, RSS, etc.)
  • Experience hiring PhD-level researchers or highly specialized engineers
  • Background in startup environments or early-stage team building
  • Experience with advanced sourcing tools, automation, or custom workflows

Who You Are:

• Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.
• Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.
• Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people.
• Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence.

Equal Opportunity & Pay Transparency

World Labs is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected under applicable law. We welcome all qualified applicants and are committed to providing reasonable accommodations throughout the hiring process upon request.

In accordance with California law, we disclose the following:

• Pay Range: $180,000-$225,000 base salary (good-faith estimate for San Francisco Bay Area upon hire; actual offer based on experience, skills, and qualifications)
• Total Compensation: Base salary plus equity awards and annual performance bonus
• Salary History: We do not request or consider prior compensation in making offers

Compliance:

• Cal. Lab. Code §432.3 (pay scale disclosure & salary history ban); Cal. Lab. Code §1197.5 (Equal Pay Act); Cal. Gov. Code §12940 (FEHA); 42 U.S.C. §2000e (Title VII); 29 U.S.C. §621 (ADEA); 42 U.S.C. §12101 (ADA)
• Accommodations & inquiries: talent@worldlabs.ai

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Navigation System Architecture & Design:

Establish navigation performance requirements and error budgets for safety-critical applications. Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software components. Design detailed software architecture for state estimation implementations, including module interfaces and data flow.

Algorithm Development & Implementation:

Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approaches. Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithms. Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environments. Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systems. Implement integrity monitoring and protection level calculations for safety-critical operations.

Certification & Verification:

Develop verification and validation test plans for navigation algorithms. Conduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluation. Document navigation system design, requirements allocation, and compliance evidence. Support safety assessment activities including failure modes and effects analysis.

Technical Leadership:

Provide technical guidance on navigation architecture and state estimation approaches. Support trade studies evaluating navigation sensor suites and fusion strategies. Mentor junior engineers on state estimation theory and implementation.

Required qualifications:

• MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related field
• 15+ years of experience developing state estimation algorithms for aerospace navigation applications
• Demonstrated experience implementing GNSS/INS integration solutions
• Experience with safety-critical system development and certification processes
• Deep understanding of state estimation theory
• Experience implementing multi-sensor fusion algorithms in production systems
• Strong background in inertial navigation, GNSS positioning, and sensor error modeling
• Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysis
• Understanding of integrity monitoring, protection levels, and safety assessment methods
• Experience with requirements management and verification/validation processes for certifiable systems
• Understanding of GPS/GNSS signal structure, error sources, and performance characteristics
• Knowledge of IMU error models, calibration, and Allan variance analysis
• Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.)
• Understanding of navigation performance metrics (accuracy, integrity, continuity, availability)

Preferred qualifications:

• PhD in relevant field with focus on state estimation or navigation
• Direct involvement in certified navigation system development from requirements through flight test
• Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.)
• Publications or patents in navigation or state estimation
• Experience with GPS/GNSS jamming and spoofing mitigation techniques
• Clearance eligible or active security clearance

The salary for this position is $270,000 - $400,000 a year.

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You will work at the intersection of heat transfer, materials science, and optical engineering to push the boundaries of receiver efficiency, durability, and cost-effectiveness.

Key responsibilities include:

• Leading the end-to-end design and development of high-temperature solar receivers optimized for solar field integration
• Developing thermal and optical models to predict receiver performance, including flux distribution, heat transfer efficiency, and thermal stress analysis
• Selecting and qualifying materials capable of withstanding extreme temperatures (800°C–1000°C+), thermal cycling, and high solar flux environments
• Designing receiver geometries (cavity, external, tubular, particle-based) to maximize energy absorption while minimizing thermal losses and mechanical fatigue
• Collaborating with solar collection and controls teams to optimize aiming strategies and flux distribution on receiver surfaces
• Interfacing with heat exchanger and thermal storage engineers to ensure seamless integration of receiver output with downstream systems
• Developing and executing testing protocols for receiver prototypes, including high-flux testing and accelerated life cycle evaluation
• Driving design-for-manufacturing initiatives to reduce receiver cost and improve producibility at scale
• Staying current with advances in receiver technology, high-temperature coatings, and selective absorber materials

Required qualifications include:

• A bachelor's degree in Mechanical Engineering, Aerospace Engineering, Materials Science, or related field; a master's or PhD is preferred
• 7+ years of experience in thermal systems design, with significant focus on high-temperature receiver or heat exchanger development
• Demonstrated expertise in solar thermal receiver design for tower-based or central receiver systems
• Strong background in heat transfer (conduction, convection, radiation), thermodynamics, and fluid mechanics
• Proficiency with thermal simulation tools (ANSYS, COMSOL, SolarPILOT, or equivalent)
• Experience with high-temperature materials including ceramics, refractory metals, and advanced alloys
• Hands-on experience taking receiver designs from concept through prototype testing and into production

Preferred qualifications include:

• Experience with molten salt, liquid sodium, or particle-based heat transfer media
• Knowledge of selective absorber coatings and high-temperature surface treatments
• Familiarity with optical modeling and ray-tracing software for flux analysis
• Background in solar field optimization and aiming point strategies
• Publications or patents in solar thermal receiver technology

Additional information:

• Competitive salary and equity options
• Comprehensive benefits package, including health, dental, and retirement plans
• Dynamic work environment that fosters creativity and innovation
• Opportunities for professional growth and development in a rapidly evolving industry
• Relocation assistance

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Your work may involve brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space. You will prototype and develop these ideas with the rest of the team, contributing directly to Gemini Diffusion research. You will solve key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps. You will rigorously validate the theoretical and practical impact of our work at a large scale. You will work collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production. You will advance the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models. You will bring deep scientific expertise into our projects, sharing your insights and knowledge with other researchers and engineers.

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In this role, you will make key contributions to the latest research developed in the Gemini audio pillar, including:

Unlocking new audio capabilities within the model, both in pre-training and post-training. Improving quality of models for understanding and generation, including research to improve our tokenizers, better techniques for generation quality, and looking at joint audio and visual representations. Better evaluation methods (human, auto raters, automated metrics) to measure quality of open-ended tasks.

To succeed in this role, you should have a PhD in Computer Science, Computer Vision, Speech Processing, or Machine Learning related field, experience working with LLMs, and audio or video understanding and/or generation experience. A proven track record of research and publications in areas such as audio generation, video generation, LLMs, and a real passion for AI are also advantages.

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We are seeking 2 Research Engineers for the Frontier Safety Risk Assessment team within the AGI Safety and Alignment Team.

As a Research Engineer, you will contribute novel research towards our ability to measure and assess risk from frontier models. This might include:

• Identifying new risk pathways within current areas (loss of control, ML R&D, cyber, CBRN, harmful manipulation) or in new ones;
• Conceiving of, designing, and developing new ways to measure pre-mitigation and post-mitigation risk;
• Forecasting and scenario planning for future risks which are not yet material.

Your work will involve complex conceptual thinking as well as engineering. You should be comfortable with research that is uncertain, under-constrained, and which does not have an achievable “right answer”. You should also be skilled at engineering, especially using Python, and able to rapidly familiarise yourself with internal and external codebases. Lastly, you should be able to adapt to pragmatic constraints around compute and researcher time that require us to prioritise effort based on the value of information.

Although this job description is written for a Research Engineer, all members of this team are better thought of as members of technical staff. We expect everyone to contribute to the research as well as the engineering and to be strong in both areas.

The role will mostly depend on your general ability to assess and manage future risks, rather than from specialist knowledge within the risk domains, but insofar as specialist knowledge is helpful, knowledge in ML R&D and loss of control as risk domains are likely the most valuable.

About You

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• You have extensive research experience with deep learning and/or foundation models (for example, but not necessarily, a PhD in machine learning).
• You are adept at generating ideas and designing experiments, and implementing these in Python with real AI systems.
• You are keen to address risks from foundation models, and have thought about how to do so. You plan for your research to impact production systems on a timescale between “immediately” and “a few years”.
• You are excited to work with strong contributors to make progress towards a shared ambitious goal.
• With strong, clear communication skills, you are confident engaging technical stakeholders to share research insights tailored to their background.

In addition, any of the following would be an advantage:

• Experience in areas such as frontier risk assessment and/or mitigations, safety, and alignment.
• Engineering experience with LLM training and inference.
• PhD in Computer Science or Machine Learning related field.
• A track record of publications at venues such as NeurIPS, ICLR, ICML, RL/DL, EMNLP, AAAI and UAI.
• Experience with collaborating or leading an applied research project.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc.

We are also open to relocating candidates and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

The US base salary range for this full-time position is between $136,000 - $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

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About the Team

We build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.

Microsoft Superintelligence Team

Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!

Responsibilities

Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

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Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact. Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images. Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust. Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs. Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web. Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems. Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology. Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property. Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs. Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively. Identifies and solves significant business problems using novel, scalable, and data-driven solutions. Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work. Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review. Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols. Communicates clearly through design documentation, progress updates, and presentations to executives and customers. Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.

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We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.

This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.

In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.

Microsoft Superintelligence Team Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.

Responsibilities Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.

Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.

Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.

Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.

Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.

Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.

Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.

Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

Qualifications Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Additional or Preferred Qualifications Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Strong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.

Proven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.

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As a Societal Impacts research scientist on the Models Research Pod, you'll close the loop between observing Claude's behavior and improving it at the model level. You'll use observational tools like Clio to analyse real-world usage patterns and build evaluations that assess whether Claude provides safe responses aligned with its Constitution.

Responsibilities:

• Using observational tools like Clio to analyse real-world usage patterns and surface insights about how people interact with Claude.
• Building and running evaluations to assess Claude's behaviour across key dimensions of its Constitution, such as safety and quality of advice in high-stakes situations.
• Partnering closely with fine-tuning, safeguards, policy, and interpretability teams to translate research insights into model improvements.
• Generating insights about the societal impact of Anthropic's systems and using this understanding to inform company strategy, research priorities, and policy positions.
• Sharing your work through research publications and external presentations, and developing tools and frameworks that make AI systems more understandable to policymakers, academics, and civil society.

You may be a good fit if:

• You have experience working with machine learning systems and are comfortable with technical infrastructure for interfacing with models.
• You have an interest in societal impacts research; prior experience in this area is a plus but not required.
• You're adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda.
• You're skilled at writing up and communicating your results, even when they're null or unexpected.
• You find it exciting to partner with colleagues across teams on large-scale projects where the whole company contributes to building and analysing AI systems.
• You have a background in machine learning, data science, or another technical field that involves generating insights from complex systems.
• You're passionate about translating research insights into actionable recommendations for improving AI systems and informing policy.
• For senior candidates: you're willing to do hands-on work while also helping shape research direction, and you may be interested in management opportunities down the line.

Some examples of our work:

• Clio: A system for privacy-preserving insights into real-world AI use
• Values in the Wild
• How People Use Claude for Support, Advice, and Companionship
• Economic Index
• How AI is Transforming Work at Anthropic
• Education Report: How University Students Use Claude
• The Capacity for Moral Self-Correction in Large Language Models
• Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviours, and Lessons Learned
• Challenges in evaluating AI systems
• Towards Measuring the Representation of Subjective Global Opinions in Language Models
• Collective Constitutional AI: Aligning a Language Model with Public Input

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New York City; San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Safety Systems

Compensation

• $380K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

Safety Systems sits at the forefront of OpenAI’s mission to build and deploy safe AGI, ensuring our most capable models can be released responsibly and for the benefit of society. Within Safety Systems, we are building a misalignment research team to focus on the most pressing problems for the future of AGI. Our mandate is to identify, quantify, and understand future AGI misalignment risks far in advance of when they can pose harm.

The work of this research taskforce spans four pillars:

1. Worst‑Case Demonstrations – Craft compelling, reality‑anchored demos that reveal how AI systems can go wrong. We focus especially on high importance cases where misaligned AGI could pursue goals at odds with human well being.

1. Adversarial & Frontier Safety Evaluations – Transform those demos into rigorous, repeatable evaluations that measure dangerous capabilities and residual risks. Topics of interest include deceptive behavior, scheming, reward hacking, deception in reasoning, and power-seeking, along with other related areas.

1. System‑Level Stress Testing – Build automated infrastructure to probe entire product stacks, assessing end‑to‑end robustness under extreme conditions. We treat misalignment as an evolving adversary, escalating tests until we find breaking points even as systems continue to improve.

1. Alignment Stress‑Testing Research – Investigate why mitigations break, publishing insights that shape strategy and next‑generation safeguards. We collaborate with other labs when useful and actively share misalignment findings to accelerate collective progress.

About the Role

We are seeking a Senior Researcher who is passionate about red‑teaming and AI safety. In this role you will design and execute cutting‑edge attacks, build adversarial evaluations, and advance our understanding of how safety measures can fail—and how to fix them. Your insights will directly influence OpenAI’s product launches and long‑term safety roadmap.

In this role, you will

• Design and implement worst‑case demonstrations that make AGI alignment risks concrete for stakeholders, focused on high stakes use cases described above.

• Develop adversarial and system‑level evaluations grounded in those demonstrations, driving adoption across OpenAI.

• Create automated tools and infrastructure to scale automated red‑teaming and stress testing.

• Conduct research on failure modes of alignment techniques and propose improvements.

• Publish influential internal or external papers that shift safety strategy or industry practice. We aim to concretely reduce existential AI risk.

• Partner with engineering, research, policy, and legal teams to integrate findings into product safeguards and governance processes.

• Mentor engineers and researchers, fostering a culture of rigorous, impact‑oriented safety work.

You might thrive in this role if you

• Already are thinking about these problems night and day, and share our mission to build safe, universally beneficial AGI and align with the OpenAI Charter.

• Have 4+ years of experience in AI red‑teaming, security research, adversarial ML, or related safety fields.

• Possess a strong research track record—publications, open‑source projects, or high‑impact internal work—demonstrating creativity in uncovering and exploiting system weaknesses.

• Are fluent in modern ML / AI techniques and comfortable hacking on large‑scale codebases and evaluation infrastructure.

• Communicate clearly with both technical and non‑technical audiences, translating complex findings into actionable recommendations.

• Enjoy collaboration and can drive cross‑functional projects that span research, engineering, and policy.

• Hold a Ph.D., master’s degree, or equivalent experience in computer science, machine learning, security, or a related field.

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San Mateo, CA, United States

Early Career

ID: 5825

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.

We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen in making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnered with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and craft the product roadmap, and prioritize, build data products, and measure impact on our community of players and developers.

WHY GENERATIVE AI?

Our team’s mission is to enable Roblox Creators to bring GenAI capabilities to millions of users. We drive this innovation with a core commitment to safety, responsibility, and quality.

As a Data Scientist, you will play a critical role in evaluation and optimization for user-facing GenAI systems (such as text, image, video, 3D, 4D). You will define how we measure safety, responsibility, quality, and efficiency. You will combine annotation analysis, design of experiments, causal inference, model-based evaluation methods (such as LLM-as-a-judge), optimization algorithm, and AI models to drive product decisions and model improvements.

You Will:

• Develop Evaluation Frameworks: Design and operationalize rigorous evaluation systems for either GenAI features (text, image, video, 3D, 4D). This includes eval experiment design, dataset design, label reliability analysis, and implementing and finetuning LLM-as-judge methods.

• Run Rigorous Experiments: Conduct online experiments (A/B tests) and causal inference to quantify the impact of GenAI features. You will identify opportunities, measure lift, and ensure statistical rigor.

• Define Success Metrics: Partner with cross-functional teams to define leading/lagging indicators for GenAI feature user satisfaction, business success, and safety.

• Build Automated Systems: Research and apply state-of-the-art methodologies to build reproducible evaluation tooling that lift rigor and efficiency across the company.

• Conduct Applied Research at the Frontier: Maintain an active pulse on the intersection of Gen AI and Data Science. You will innovate on methodology and techniques to solve unique business challenges while contributing to the broader field in the technical community.

You Have:

• Possess or pursuing a PhD or equivalent in Statistics, Economics, Computer Science, Applied Math, Physics, Engineering, or a related quantitative field.

• Technical Proficiency: Strong proficiency in SQL (Hive/Spark) for manipulating large datasets and scripting languages (Python or R) for analysis and modeling.

• Experimentation and Causal Inference: A solid grounding in experimentation, causal inference, and statistical analysis, including test design and metric design for feature impact.

• Problem Solving: A demonstrated track record of framing ambiguous problems, designing analytical approaches, and solving open-ended data science problems that drive business impact.

• Learning Agility: Ability to effectively and responsibly use AI tools to enhance productivity and a passion for continuously improving methods in a fast-evolving field.

• GenAI Familiarity: Familiarity with GenAI models and safety/quality evaluation methods. Expertise in the model training lifecycle is a plus (e.g., fine-tuning, RLHF, or synthetic data generation).

• Applied Research Background: A track record of applied research or publications in relevant technical fields is highly valued.

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.

Annual Salary Range

$185,860—$221,380 USD

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

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Microsoft are looking for a talented Senior Applied Scientist at their Suzhou office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising the online advertising platform and service. You'll work directly with leadership to shape the company's direction in the advertising industry.

About the Role

As a Senior Applied Scientist, you will play a key role in driving algorithmic and modeling improvement to the system. You will analyze performance and identify opportunities based on offline and online testing. You will develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads. You will have good communication, collaboration, and analytical skills.

Accountabilities

• Play a key role in driving algorithmic and modeling improvement to the system.
• Analyze performance and identify opportunities based on offline and online testing.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Technical skills:

• Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Experience conducting research as part of a research program (in academic or industry settings).

Personal attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.

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Microsoft are looking for a talented Senior Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising the online advertising platform and service. You'll work directly with leadership to shape the company's direction in the advertising market.

About the Role

As a Senior Applied Scientist, you will play a key role in driving algorithmic and modeling improvement to the system. You will analyze performance and identify opportunities based on offline and online testing. You will develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads. You will have good communication, collaboration, and analytical skills.

Accountabilities

• Play a key role in driving algorithmic and modeling improvement to the system.
• Analyze performance and identify opportunities based on offline and online testing.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Technical skills:

• Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Experience conducting research as part of a research program (in academic or industry settings).

Personal attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

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Microsoft AI are looking for a talented Principal Applied Scientist at their Hyderabad office. This role sits at the heart of shaping and improving sports experiences on Bing. You will own end-to-end outcomes: turn ambiguous product questions into measurable hypotheses, define success metrics, design experiments, and ship data-driven ML solutions that move customer and business KPIs.

About the Role

We are seeking an experienced, self-directed Principal Applied Data Scientist to shape and improve sports experiences on Bing. In this individual contributor role, you will own end-to-end outcomes: turn ambiguous product questions into measurable hypotheses, define success metrics, design experiments, and ship data-driven ML solutions that move customer and business KPIs. You will apply modern NLP/IR and multimodal methods—including training and adapting Large Language Models (LLMs) and Small Language Models (SLMs)—to deliver accurate, fresh, and helpful sports answers and discovery experiences at global scale.

Accountabilities

• Define north-star metrics and guardrails; build measurement plans, offline scorecards, and online A/B tests; interpret results and drive clear ship/iterate decisions.
• Build, train, and adapt LLM/SLM solutions for sports scenarios (prompting, supervised fine-tuning, distillation, and domain adaptation), using disciplined evaluation and error analysis to improve quality, latency, and cost.

The Candidate we're looking for

Experience:

• 6+ years related experience (e.g., statistics, predictive analytics, research).

Technical skills:

• Proficiency in Python (and one of C++/C#/Java preferred) and deep learning frameworks (e.g., PyTorch, TensorFlow); experience with distributed training/inference is a plus.

Personal attributes:

• Demonstrated ability to lead through influence as a senior IC: independently define strategy, drive execution across teams, and deliver measurable impact.

Benefits

• Starting January 26, 2026, Microsoft AI employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.

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What you'll do

Research & Development

• Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO)
• Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products

What you need

• Proven experience with large-scale LLMs and Deep Learning systems

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What you'll do

• Define and execute the macro research direction across multiple modalities, including post-training LLMs for agent trajectories and future mid-training initiatives
• Lead strategic research planning and roadmap development to advance Sonar model capabilities
• Drive innovation in supervised and reinforcement learning techniques for query answering
• Collaborate with leadership to align research priorities with product and business objectives

What you need

• Minimum of 5 years of experience working on relevant AI/ML projects with 3+ years in a technical leadership role
• Proven track record of leading and mentoring technical and research teams
• A Computer Science graduate degree at a premier academic institution
• Deep expertise with large-scale LLMs and Deep Learning systems
• Strong programming skills with versatility across multiple languages and frameworks
• Demonstrated ability to set technical vision and drive execution
• Experience with pre-training and post-training techniques (self-supervised learning along with SFT/DPO/GRPO/PPO)
• Self-starter with exceptional ownership mentality and ability to work in ambiguous environments
• Passion for solving challenging problems and pushing the boundaries of AI research

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