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Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop , both during production RL training and after. You'll also take a cross-organisational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.

This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.

Responsibilities:

• Build new novel and long-horizon evaluations
• Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training
• Lead strategic evaluation coverage across the company
• Shape the evaluation narrative for model releases
• Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research
• Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules
• Build and maintain relationships across Anthropic's research organisation to ensure evaluation insights inform training and deployment decisions
• Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices

You may be a good fit if you:

• Have significant experience designing and running evaluations for large language models or similar complex ML systems
• Have led technical projects or teams, either formally or through sustained ownership of critical research directions
• Are equally comfortable designing experiments and writing code,you can move between research and implementation fluidly
• Think strategically about what to measure and why, not just how to measure it
• Can synthesise information across multiple teams and workstreams to form a coherent picture of model capabilities
• Communicate complex technical findings clearly to both technical and non-technical audiences
• Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings
• Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed

Strong candidates may also have:

• Experience building evaluations for long-horizon or agentic tasks
• Deep familiarity with Reinforcement Learning training dynamics and how model behaviour changes during training
• Published research in machine learning evaluation, benchmarking, or related areas
• Experience with safety evaluation frameworks and red teaming methodologies
• Background in psychometrics, experimental psychology, or other measurement-focused disciplines
• A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment
• Experience managing or mentoring researchers and engineers

Representative projects:

• Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions
• Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge
• Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritising new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product
• Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterise model capabilities and limitations
• Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks
• Leading a team effort to build reusable evaluation infrastructure that serves multiple teams across the research organisation

The annual compensation range for this role is $850,000.

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As a Manager, Software Engineering, you will be responsible for demonstrating end-to-end outcome ownership of a major system within an integrated product, and the team responsible for building and maintaining it. You will contribute as a team lead to the rapid architecting, design, delivery, support, and evolution of next-generation autonomous platforms through their entire product life-cycle.

Key responsibilities include:

• Empathizing with end-users and driving solutions that balance their needs with external constraints, restrictions, and requirements in a multi-stakeholder environment
• Being accountable for software-enabled solutions that are deployed to customers, optimizing for the delivery of value to the end-user
• Collaborating with your Technical Lead to architect scalable software that rapidly delivers capability beyond the scope of current platforms, with a clear path for both architecture and capability evolution over time
• Coordinating your team's roadmap and execution with other teams across Anduril, with the aim of developing components that are reusable across multiple Anduril product lines
• Contributing to the design, implementation, and execution of development processes for the initial delivery and subsequent iteration of vehicle and mission software, including full lifecycle testing, monitoring, and operation
• Managing a 6-18 month roadmap for your team, nested within broader organisational roadmap
• Managing an allocated budget for your team
• Managing programmatic risk for your team, and collaborating with your Technical Lead to manage technical risk, including sound and timely decision making
• Leading by example as a technically competent, trustworthy, and accountable team lead
• Communicating organisational vision, strategy, and direction to your team
• Defining, documenting, gaining consensus for, and communicating appropriate goals and plans for your team, derived from broader organisational vision, strategy, and priorities
• Building your team through mentoring, professional development, career management, and collaboration with Anduril's recruiting and people functions
• Working as a leader of a multi-disciplinary engineering team of 4-10 members, including as a mentor and manager for Engineers from differing backgrounds
• Reporting to a manager who may or may not have a background in software engineering
• Traveling to co-locate with end-users and/or other teams up to 20% of the time

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This position is needed to add to our Voice Connectivity Trust team to enable Twilio to better support our customers using Voice in their solutions.

As a Software Engineer on this team, you will participate in all phases of the software development life cycle, including requirements gathering with Product Managers, technical design, estimations, sprint planning, coding, testing, deployments, and on-call support.

In this role, you'll:

• Design and implement real-time services with high throughput and low latency requirements, verify, deploy, and operationalize them

• Work closely with stakeholders to understand customer needs and devise and deliver simple, robust, and scalable solutions

• Be comfortable expressing thoughts and ideas as detailed prose and use it as an effective means to collaborate with leads, architects, and cross-functional teams

• Embrace the challenge of scaling a complex distributed platform with points of presence globally, each one concerned with high availability, high reliability, high throughput, low latency, and media fidelity

• Figure out novel ways of solving customer problems for the Voice channel

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply.

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This role focuses on building, deploying, and managing internal Windows and Linux infrastructure while collaborating with other teams to develop scalable solutions.

Responsibilities:

• Building, managing, and supporting complex application stacks on Windows and Linux Servers.
• Providing Windows and Linux troubleshooting and technical support.
• Deploy, configure and support VMware technologies, including vCenter, ESX and Horizon.
• Use Puppet Enterprise to automate and manage configurations.
• Working with other engineering teams and third-party vendors to implement scalable solutions.
• Ensuring compliance by collaborating with internal audit and compliance teams.
• Developing and maintaining standard operating procedures.
• Participating in a 24/7 on-call support rotation.
• Managing and monitoring all installed Windows and Linux systems and infrastructure.
• Installing, configuring, testing, and maintaining operating systems and system management tools.
• Proactively ensuring high levels of system availability and reliability.
• Monitoring and optimizing application performance, identifying bottlenecks, and collaborating with developers to implement solutions.
• Writing and maintaining custom scripts to improve system efficiency and automation.

Required Qualifications:

• Deep understanding of infrastructure management and automation
• 3 to 5 years of experience in the following:
• Systems Engineering for Corporate Infrastructure.
• Managing large-scale Windows and Linux server environments.
• Virtualization at scale.
• Configuration Management.
• Managing scalable storage solutions, preferably NetApp.
• Developing and maintaining performance metrics for systems.
• Strong understanding of Puppet Enterprise and Puppet Open Source.
• Strong understanding of basic networking concepts.
• Proficient with using Puppet to automate and manage configurations.
• Ability to translate business needs into technical solutions.
• Outstanding analytical and problem-solving skills.
• Strong written and verbal communication skills.
• Experience writing technical design documents and maintaining documentation.
• Familiarity with working in a source-controlled environment.
• Proficiency in scripting languages such as Bash, Python, or Perl.
• Experience with VMware services, including VMware data center virtualization and VMware Horizon.

Basic Qualifications:

• Familiarity with DevOps practices and CI/CD tools.
• Knowledge of orchestration tools.

Compensation and Benefits:

$162,000 - $226,000

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

ITAR Requirements:

To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

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Responsibilities:

• Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).
• Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data.
• Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.
• Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.
• Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.
• Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.

Basic Qualifications:

• Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.
• Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.
• Experience developing or working with large-scale distributed machine learning systems.
• Ability to deliver optimal end-to-end user experiences.
• Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.

Preferred Skills and Experience:

• Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.
• Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.
• Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).
• Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).

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This role blends hands-on technical expertise with leadership responsibilities, guiding a team of Desktop Engineers and Support Analysts while driving modernization initiatives across device management, imaging, patching, software deployment, and endpoint security.

The ideal candidate is a forward-thinking technical leader with strong communication skills, deep experience in modern endpoint management platforms, and a passion for automation, standardization, and continuous improvement.

Responsibilities:

• Oversee the engineering, automation, and lifecycle management of all corporate endpoints
• Guide a team of Desktop Engineers and Support Analysts
• Drive modernization initiatives across device management, imaging, patching, software deployment, and endpoint security

Required qualifications:

• 5+ years of experience in Desktop Engineering, Endpoint Management, or EUC roles
• 2+ years in a technical lead or mentorship capacity
• Deep experience with modern endpoint management platforms (Intune, Jamf, SCCM/MECM)

Preferred qualifications:

• Experience with Conditional Access, identity-driven security, and Zero Trust concepts
• Familiarity with endpoint analytics, telemetry, or monitoring tools
• Experience with virtual desktop platforms (Azure Virtual Desktop, Citrix, VMware Horizon)
• Relevant certifications (Microsoft, Jamf, ITIL, CompTIA)

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Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.

We are a small company with under 100 employees, operating with the energy of a startup. However, we're also publicly traded, which means our employees get access to the liquidity of our publicly-traded equity.

As a Senior DevOps Lead at Cyngn, you will play a vital role in architecting and managing infrastructure across cloud and autonomous vehicle systems. This position combines traditional cloud DevOps leadership with specialized expertise in robotics and autonomous systems infrastructure.

Responsibilities

• Lead and architect cloud and vehicle infrastructure initiatives across AWS and ROS/Linux environments
• Design and implement scalable solutions for both cloud services and autonomous vehicle systems
• Establish and maintain DevOps best practices, CI/CD pipelines, and infrastructure as code
• Drive observability, monitoring, and incident response strategies
• Optimize performance and cost efficiency of cloud and edge computing resources
• Mentor team members and foster a developer-friendly environment
• Manage on-call rotations and incident response processes
• Architect solutions for processing and storing large-scale vehicle telemetry data
• Lead security initiatives and compliance efforts across infrastructure

Requirements

• 10+ years of relevant DevOps/Infrastructure experience
• Proven track record as a technical lead in platform or infrastructure teams
• Advanced expertise in AWS services, infrastructure as code (Terraform), and Kubernetes
• Strong experience with service mesh (Istio) and Helm/Kustomize
• Deep understanding of ROS/ROS2 and Linux kernel configurations
• Experience with GPU configurations and ML infrastructure
• Expertise in ARM and NVIDIA CUDA platform configurations
• Strong programming skills in Python and shell scripting
• Experience with infrastructure automation (Ansible)
• Expertise in CI/CD tools (Jenkins, GitHub Actions)
• Strong system architecture and design skills
• Excellence in technical documentation
• Outstanding problem-solving abilities
• Strong leadership and mentoring capabilities

Nice to haves

• Experience with autonomous vehicle systems
• Track record of optimizing GPU-based ML infrastructure
• Experience with large-scale IoT deployments
• Contributions to open-source projects
• Experience with real-time systems and low-latency requirements
• Expertise in security implementations including SSO, IdP, and AWS Cognito
• Experience with JFrog artifactory and container registry management
• Proficiency in AWS IoT Greengrass
• Experience with container resource management on edge devices
• Understanding of CPU affinity and priority scheduling
• Track record of implementing cost optimization strategies
• Experience with scaling systems both horizontally and vertically

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)
• Life, Short-term, and long-term disability insurance (Cyngn funds 100% of premiums)
• Company 401(k)
• Commuter Benefits
• Flexible vacation policy
• Sabbatical leave opportunity after five years with the company
• Paid Parental Leave
• Daily lunches for in-office employees
• Monthly meal and tech allowances for remote employees

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BlackRock is seeking a Director, Head of Asset Level Analytics to lead the buildout of front-office capabilities to support deal & asset level analysis for corporate and asset-based underlying. This role will be part of the Private Markets Analytics Product team, which is focused on building the premier private markets analytics platform to support BlackRock's 2030 strategy.

The ideal candidate will combine a credit analytics background, including a strong understanding of the private credit business context and resulting use-cases, with horizontal leadership and coordination skills to bring multiple groups together. They will also need excellent problem-solving skills that bridge technical and organizational aspects to move forward at pace.

Key Responsibilities

• Set Product strategy: drive asset level analytics product strategy, leveraging a deep understanding of client needs (BlackRock risk and investment teams focused on Private credit, Asset-based Finance, Infrastructure) as well as growing number of Aladdin clients that are leveraging Private Credit investment book of record functionality.

• Lead Analytics Product Delivery: coordinate analytics delivery across the Aladdin value-chain to ensure quality end user experience – from data to models to analytics factory to APIs / UX, connecting people across Product, Engineering and Data organizations within Aladdin.

• Team development: lead a broad virtual team focused on asset level analytics – across many teams within Aladdin helping embed the deal level mindset and language to connect better with end-users in this space.

• Stakeholder engagement: build strong relationships across BlackRock teams, with particular focus on PFS, RQA, PMG and GIP.

Required Skills

• Industry experience: 10+ years of experience in credit with material exposure to unlisted credit (e.g. private credit underwriting, credit agency, bank lending, credit risk advisory).

• Horizontal leadership: demonstrated ability to lead across multiple verticals and matrixed organization structures, connecting BlackRock investment teams, client-facing teams as well as Product, Engineering and Data teams across Aladdin.

• Critical thinking and problem solving: ability frame problems and to define path forward in the absence of an industry standard.

• Communication skills: demonstrated ability to simplify complex problems and crystallize proposed solutions in writing is critical given the number of teams involved and complexity of the content.

• Client-delivery orientation: ability to listen and fully understand client needs (starting with BlackRock) is critical, to ensure the solutions designed are geared towards delightful client experience with analytics.

• AI proficiency: hands-on comfort using AI tools (e.g., prompt-based research, synthesis, data exploration – with awareness of AI limitations) and prompt engineering fundamentals (ability to create, test, iterate, and evaluate prompts/workflows to achieve consistent outputs).

Preferred Qualifications and Skills

• CFA or CAIA qualification preferred.

• Bachelor's degree in a relevant field and advanced degree preferred.

• Proficiency in Microsoft Office suite, particularly Excel, PowerPoint and Word.

• Prior exposure to private markets investment technology platforms (e.g. Aladdin/eFront, Chronograph, BlackMountain) preferred.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

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San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $385K • 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

The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.

Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.

This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.

About the Role

We’re looking for experienced Software Engineers to help build OpenAI’s foundational ads ranking and recommendation systems—the ML and AI platforms that determine how monetized experiences are selected, ordered, and optimized across OpenAI products.

In this role, you’ll architect and implement large-scale, high-performance ML-driven systems with rigorous requirements around latency, correctness, safety, privacy, and continuous improvement. You’ll work on modern, transformer- and LLM-inspired architectures that move beyond traditional feature engineering toward more expressive, context-aware decisioning. Your work will have a direct revenue impact and make ChatGPT and other products accessible to more people with fewer usage limits or without having to pay.

This is a deeply technical, 0→1 founding-stage role where you’ll operate across backend engineering, systems design, and applied AI/ML to help define the next generation of AI-native monetization and recommendation platforms.

This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees.

In this role, you will:

• Architect, build, and evolve large-scale ads ranking and recommendation systems using modern ML and AI techniques

• Design and productionize LLM- and transformer-inspired models that leverage sequential signals, long-horizon context, and sparse or delayed feedback.

• Develop model-driven decision logic and inference pipelines that operate under real-world constraints around performance, reliability, and privacy.

• Partner closely with Product, Design, and Research to define requirements and translate ambiguous product goals into scalable ML systems.

• Prototype, experiment, and rapidly iterate on new model architectures and training approaches to improve relevance, quality, and efficiency.

• Build services and infrastructure that support training, evaluation, online inference, and continuous optimization of ML models.

• Establish strong measurement, experimentation, and debugging practices to understand model behavior and system-level outcomes.

• Contribute to technical strategy and help shape the long-term evolution of OpenAI’s monetization and recommendation stack.

• Embed safety, fairness, and policy considerations directly into model design and system architecture from first principles.

You might thrive in this role if you:

• Have 6+ years of experience building and scaling ML-powered systems in production environments.

• Have worked on ranking, recommendation, ads, marketplaces, or large-scale ML inference systems.

• Are comfortable operating across the full stack — from model development to backend services and production deployment.

• Enjoy deeply technical 0→1 problem spaces where architecture, strategy, and implementation overlap.

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Race IT Technical Support Engineer

Full Time

Signes, France

Young Professional

July 14, 2025

Participate in the development of Information Technology plans, strategies and methods, which maximize the department's contribution towards meeting overall company goals and objectives.

Main Tasks

• Setup, Support, Operate and Maintain the IT infrastructure in racing environment
• Travel with our other IT team at track event and testing facilities
• Setup/maintenance trackside IT systems at race & test events
• Monitor performance of Data transferring and H/W reliability
• Assist colleagues with day-to-day all kind of IT technical challenges in race & test events
• Additional related IT duties may be assigned

Qualifications

• Bachelor's degree in Computer Science, Engineering or equivalent
• 3+ years experience as Technical Support Engineer
• Knowledge in: Active Directory, M365 and VMare

Our Offer

• Secure and long-term employment relationship
• Market and performance-related remuneration
• Training and career development
• Working in an international and dynamic environment
• Attractive benefits

https://motorsporthyundai.career.softgarden.de/jobs/57789748/Race-IT-Technical-Support-Engineer/

Race IT Technical Support Engineer

Signes, France

Full Time

July 14, 2025

Main Tasks

Our Offer

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