You will coordinate and prioritize workload within a large team, provide on-the-job support to contingent staff, and communicate run performance, KPIs, and operational updates to stakeholders. You will work closely with hub specialists and scientists as well as supporting functional spaces within the Precision Genomics program.

To be successful in this role, you will possess a Bachelor's degree and knowledge of next-generation sequencing (NGS) technologies, platforms, and associated workflows. You will also have strong molecular biology foundation with the ability to troubleshoot workflows, interpret data, and apply sound scientific judgment. Additionally, you will have demonstrated good laboratory technique, including accurate pipetting, contamination control, and consistent execution of SOPs.

Preferred qualifications include a Master's degree in Biology, Chemistry, or a related field with 1+ year of relevant experience, or a Bachelor's degree with 4+ years of related experience in academia or industry. Experience operating NGS instruments (Illumina preferred) in research or production settings, high-throughput automation experience, and proficiency with digital lab systems such as LIMS, sample-tracking tools, and data analysis or visualization software are also desirable.

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Training on natural and experimentally-derived data is a core aspect of how our AI models learn to generate therapeutic molecules with exceptional properties. We invest deeply in building and scaling data sources to train and evaluate our models for maximal performance. At the same time, careful validation in orthogonal, translationally-relevant assays is crucial to orient our models.

We are seeking a senior scientific leader versed in high-throughput and translational biology to drive the continued growth and impact of our Palo Alto Lab. You will be a force multiplier for our scientists and engineers, ensuring a high standard of scientific rigor and output in a fast-paced, dynamic environment. You will also interface closely with our AI team to maximize the impact of internal data on Inceptive’s foundation models.

Your Mission, should you choose to accept it - Lead development and scale-up of high-throughput assays across in vitro, cellular, and in vivo systems, leveraging multiplexed assays and laboratory automation - Define and execute a lab strategy aligned with Inceptive’s therapeutic and platform priorities, while remaining flexible as modality and partnership needs evolve - Champion an interdisciplinary culture, encouraging curiosity, rigor, and collaboration across scientific boundaries - Manage, mentor, and develop a multidisciplinary team of scientists and engineers that rapidly generates high-impact biological data to improve and validate AI design models - Oversee the development of industry-standard validation assays to keep models and data generation aligned with downstream therapeutic application

Qualifications - PhD and 6+ years of post-PhD experience in industrial research applied to drug development - Experience managing and mentoring a data-driven lab of 10+ scientists - Experience using high-throughput and/or highly multiplexed assays to generate rich datasets from mammalian cells - Proven ability to set scientific direction while also executing operationally - Deep understanding of theory, techniques, and experimental design in molecular and cellular biology - Visualization, analysis, and statistics applied to complex biological datasets - Availability to work with team members across US and Europe, with meetings starting at 7am PT - Readiness to travel several times a year for company retreats and business events - We value in-person collaboration and expect candidates to work at our lab location

Preferred skills - Translational experience with mRNA, oligonucleotides, or other genetic medicines - Expertise in immunology and/or cell therapy - Hands-on experience in RNA biology and biochemistry - Scientific programming in Python - Hands-on experience with modern data engineering workflows

Compensation $245K – $305K + Bonus + Equity

What we offer - A competitive compensation package - 30 days paid vacation per year - Comprehensive health insurance for US based Beginners - 401K with company match for US based Beginners and Direktversicherung for German Beginners - Quarterly company-wide retreats - Monthly wellness benefit - Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland - Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning & Development platform EdX and Hone - A buddy to help you get settled *Varies by country and does not apply to internships

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Anthropic is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on,from metrics and logging pipelines to distributed tracing, error analytics, alerting, and the dashboards and query interfaces that make it all actionable.

As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude. We’re building next-generation observability systems,high-throughput ingest pipelines, cost-efficient columnar storage, unified query layers across signals, and agentic diagnostic tools,to ensure that engineers can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become exponentially more complex.

Responsibilities

• Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic’s multi-cluster infrastructure

• Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organisational growth

• Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services

• Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliability targets with minimal noise

• Reduce mean time to detection and resolution by building cross-signal correlation, unified query interfaces, and AI-assisted diagnostic tooling

• Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organisation

You May Be a Good Fit If You

• Have 10+ years of relevant industry experience building and operating large-scale observability or monitoring infrastructure

• Have deep experience with at least one observability signal area (metrics, logging, tracing, or error analytics) and familiarity with the others

• Understand high-throughput data pipelines, columnar storage engines, and the tradeoffs involved in ingesting and querying telemetry data at scale

• Have experience operating or building on top of observability platforms such as Prometheus, Grafana, ClickHouse, OpenTelemetry, or similar systems

• Have strong proficiency in at least one of Python, Rust, or Go

• Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities

• Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges

Strong Candidates May Also Have

• Experience operating metrics systems at very high cardinality (hundreds of millions of active time series or more)

• Experience with log storage migrations or operating columnar databases (ClickHouse, BigQuery, or similar) for analytics workloads

• Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies

• Experience building or operating alerting platforms, on-call tooling, or SLO frameworks at scale

• Experience with Kubernetes-native monitoring, eBPF-based observability, or continuous profiling

• Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

• Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude. We're building next-generation observability systems,high-throughput ingest pipelines, cost-efficient columnar storage, unified query layers across signals, and agentic diagnostic tools,to ensure that engineers can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become exponentially more complex.

Responsibilities:

• Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure
• Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organisational growth
• Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services
• Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliability targets with minimal noise
• Reduce mean time to detection and resolution by building cross-signal correlation, unified query interfaces, and AI-assisted diagnostic tooling
• Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organisation

You May Be a Good Fit If You:

• Have 10+ years of relevant industry experience building and operating large-scale observability or monitoring infrastructure
• Have deep experience with at least one observability signal area (metrics, logging, tracing, or error analytics) and familiarity with the others
• Understand high-throughput data pipelines, columnar storage engines, and the tradeoffs involved in ingesting and querying telemetry data at scale
• Have experience operating or building on top of observability platforms such as Prometheus, Grafana, ClickHouse, OpenTelemetry, or similar systems
• Have strong proficiency in at least one of Python, Rust, or Go
• Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities
• Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges

Strong Candidates May Also Have:

• Experience operating metrics systems at very high cardinality (hundreds of millions of active time series or more)
• Experience with log storage migrations or operating columnar databases (ClickHouse, BigQuery, or similar) for analytics workloads
• Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies
• Experience building or operating alerting platforms, on-call tooling, or SLO frameworks at scale
• Experience with Kubernetes-native monitoring, eBPF-based observability, or continuous profiling
• Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting

The annual compensation range for this role is $405,000-$485,000 USD.

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Key responsibilities include:

• Designing and implementing distributed storage solutions to support scaling data-intensive AI workloads
• Contributing to the development of exabyte-scale, S3-compatible object storage
• Integrating dedicated storage clusters into diverse customer environments
• Working with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency
• Leading efforts to improve the reliability, durability, security, and observability of the storage stack
• Collaborating with operations teams to monitor, troubleshoot, and improve storage systems in production environments
• Setting the bar for developing metrics and dashboards to provide visibility into storage performance and health
• Analyzing telemetry and system data to drive improvements in throughput, latency, and resilience
• Working cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack
• Sharing knowledge and mentoring other engineers on best practices in building distributed, high-performance systems

Requirements include:

• Bachelor's, Master's, or PhD degree in Computer Science, Engineering, or a related field
• 8-10+ years of experience working in storage systems engineering or infrastructure
• Strong hands-on experience with object storage or distributed filesystems in production environments
• Experience with one or more storage protocols (e.g. S3, NFS) and file systems such as Ceph, DAOS, or similar
• Proficiency in a systems programming language such as Go, C, or Rust
• Proficiency leveraging AI tools to augment software development
• Familiarity with storage observability tools and telemetry pipelines (e.g., ClickHouse, Prometheus, Grafana)
• Experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures

The base salary range for this role is $188,000 to $275,000.

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In this role, you will:

• Establish and lead the SRE / production engineering practice for the Common Services organization, including standards for reliability, incident management, and on-call, in partnership with the central Product Engineering organization.
• Develop an Operational Excellence strategy that focuses on not only improving system performance but also monitoring and reducing operational toil
• Partner with engineering and product teams to define SLOs, SLIs, and error budgets for critical Common Services, and ensure these become part of how teams plan and make tradeoffs.
• Own and improve the incident management lifecycle for Common Services, including on-call rotations, escalation paths, incident tooling, post-incident reviews, and follow-through on corrective actions.
• Drive the observability strategy (metrics, logs, traces, dashboards, alerts) for Common Services, ensuring we have actionable visibility into the health, performance, and capacity of key systems.
• Collaborate with engineering leads to design and review architectures for reliability, scalability, resilience, and operability, including failure modes, redundancy, and graceful degradation.
• Lead efforts to automate and harden operational workflows, including deployments, rollbacks, configuration management, change management, and routine maintenance tasks.
• Build strong, trust-based relationships with partner teams and stakeholders, becoming a go-to leader for production readiness and operational risk within Common Services.
• Hire, mentor, and develop SRE and production engineering talent, fostering a culture of continuous improvement, learning from incidents, and humane on-call.
• Partner with other SRE and production engineering leaders across CoreWeave to align on global practices, tools, and reliability goals, representing the needs and constraints of Common Services.

You will be responsible for defining the reliability strategy, processes, and standards for the Common Services portfolio and driving consistent, high-quality operational practices across multiple teams.

The base salary range for this role is $206,000 to $303,000.

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About the Role:

When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.

Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs.

More resources to learn about our work:

• Our research blog - covering advances including Monosemantic Features and Circuits

• An Introduction to Interpretability from our research lead, Chris Olah

• The Urgency of Interpretability from CEO Dario Amodei

• Engineering Challenges Scaling Interpretability - directly relevant to this role

• 60 Minutes segment - Around 8:07, see a demo of tooling our team built

• New Yorker article - what it's like to work on one of AI's hardest open problems

Even if you haven't worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model:

• Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips

• Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector"

• Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission

The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI.

Responsibilities:

• Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application

• Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams

• Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers

• Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations

• Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling

You may be a good fit if you:

• Have 5-10+ years of experience building software

• Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python

• Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks

• Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions

• Prefer fast-moving collaborative projects to extensive solo efforts

• Are curious about interpretability research and its role in AI safety (though no research experience is required!)

• Care about the societal impacts and ethics of your work

• Are comfortable working closely with researchers, translating research needs into engineering solutions.

Strong candidates may also have experience with:

• Optimizing the performance of large-scale distributed systems

• Language modeling fundamentals with transformers

• High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization

• Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs

• Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges

Representative Projects:

• Building Garcon, a tool that allows researchers to easily instrument LLMs to extract internal activations

• Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them

• Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization

• Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research)

Role Specific Location Policy:

• This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $315,000-$560,000 USD

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At Cloudflare, we're on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

Emerging Technologies & Incubation (ETI)

ETI is where new and bold products are built and released within Cloudflare. Rather than being constrained by the structures which make Cloudflare a massively successful business, we are able to leverage them to deliver entirely new tools and products to our customers. Cloudflare's edge and network make it possible to solve problems at massive scale and efficiency which would be impossible for almost any other organization.

About the Team

ETI's Storage Infrastructure team is responsible for the core storage layer that underpins many of ETI's stateful services. Our scope ranges from managing the physical hardware to operating the distributed databases and storage systems built upon it. We run this infrastructure globally across Cloudflare's network, which presents unique and complex engineering puzzles. We navigate efficiently expanding storage capacity, optimizing rebuild operations, and coordinating operations across failure domains to uphold durability.

While other service teams focus on product development, our mission is to ensure the underlying storage is reliable, performant, and scalable. You'll be joining a highly motivated team that is building the next generation of distributed storage services.

Responsibilities

In this role, you will help build and operate the next generation of globally distributed storage systems. You will own your code from inception to release, delivering solutions at all layers of the stack. On any given day, you might write a design document for a new provisioning system, model failure domain dependencies across edge locations, benchmark new storage hardware, build standardized observability and runbooks for distributed database clusters, or automate operational toil through purpose-built tooling and intelligent automation.

You can expect to interact with a variety of languages and technologies including Rust, Go, Saltstack, and Terraform.

Examples of desirable skills, knowledge, and experience

• Strong programming skills with languages like Rust, Go, or Python
• A solid understanding of distributed systems concepts such as consistency, consensus, data replication, fault tolerance, and partition tolerance
• Experience with distributed databases and storage systems
• Experience with infrastructure configuration tooling and infrastructure as code
• Familiarity with storage fundamentals: block devices, filesystems, SSD characteristics
• Experience building and maintaining high-throughput, low-latency systems
• Understanding of network fundamentals as they relate to distributed storage -- bandwidth constraints, latency tradeoffs, cross-datacenter replication
• Strong written and verbal communication skills and ability to explain technical decisions clearly
• Comfortable operating in fast-paced environments with tight deadlines and evolving priorities

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!

The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave

What Makes Cloudflare Special?

We're not just a highly ambitious, large-scale technology company. We're a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo

Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare's enterprise customers--at no cost.

Athenian Project

In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1

We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here's the deal - we don't store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you'd like to be a part of? We'd love to hear from you!

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Responsibilities:

• Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
• Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
• Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI
• Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
• Collaborate to translate experimental requirements into production-ready infrastructure
• Develop large scale data pipelines to handle advanced language model training requirements
• Optimize large scale training and inference pipelines for stable and efficient reinforcement learning

You may be a good fit if you:

• Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems
• Are a strong communicator and enjoy working collaboratively
• Possess deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads
• Have experience with containerization technologies (Docker, Kubernetes) and orchestration at scale
• Have proven track record of building large-scale data pipelines and distributed storage systems
• Excel at diagnosing and resolving complex infrastructure challenges in production environments
• Can work effectively across the full ML stack from data pipelines to performance optimization
• Have experience collaborating with other researchers to scale experimental ideas
• Thrive in fast-paced environments and can rapidly iterate from experimentation to production

Strong candidates may also have:

• Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.)
• Background in building infrastructure for AI research labs or large-scale ML organizations
• Knowledge of GPU/TPU architectures and language model inference optimization
• Experience with cloud platforms (AWS, GCP) at enterprise scale
• Familiarity with VM and container orchestration
• Experience with workflow orchestration tools and experiment management systems
• History working with large scale reinforcement learning
• Comfort with large scale data pipelines (Beam, Spark, Dask, …)

The annual compensation range for this role is $350,000-$850,000 USD.

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This team moves very quickly. Claude writes a lot of the code we commit, which means the bottleneck isn't typing , it's judgment, taste, and the ability to react to what researchers need next. You'll iterate on data collection strategies to distill the knowledge of thousands of human experts around the world into our models, and you'll do it in a loop that closes in hours and days, not quarters or months.

Our work spans teaching models to use computers effectively, advancing code generation through RL, pioneering fundamental RL research for large language models, and building the scalable training methodologies behind our frontier production models. The RL org is organized around four goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model.

Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible , from realistic agentic training environments and scalable code data generation to human data collection platforms and production training operations.

Responsibilities:

• Build and extend web platforms for RL environment creation, management, and quality review , including environment configuration, versioning, and validation workflows
• Develop vendor-facing interfaces and tooling that let external partners create, submit, and iterate on training environments with minimal friction
• Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms that surface reward signal integrity issues early
• Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward hacking
• Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure
• Build and expand scalable code data generation pipelines, producing diverse programming tasks with robust reward signals across languages and difficulty levels
• Develop onboarding automation and documentation tooling so new vendors and internal users ramp up in hours, not weeks
• Partner closely with RL researchers, data operations, and vendor management to translate ambiguous requirements into well-scoped, well-designed products

You May Be a Good Fit If You:

• Have strong software engineering fundamentals and real full-stack range , you're comfortable owning a surface from database schema to frontend
• Are proficient in Python and a modern web stack (React, TypeScript, or similar)
• Have a track record of shipping systems that solved a hard problem, not just shipped on time , e.g. you built the thing that made your team 10x faster, or the internal tool nobody thought was possible
• Operate with high agency: you identify what needs to be done and drive it forward without waiting for a ticket
• Have found yourself wondering "why isn't this moving faster?" in previous roles , and then have done something about it
• Care about UX and can build interfaces that are intuitive for both technical researchers and non-technical labelers
• Communicate clearly with researchers, operations teams, and engineers, and can turn vague asks into well-scoped work
• Thrive in a fast-moving environment where priorities shift, Claude is your pair programmer, and the next problem is often one nobody has solved before
• Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute directly to it

Strong Candidates May Also Have:

• Built data collection, labeling, or annotation platforms , ideally ones that had to scale across many vendors or many task types
• Background building multi-tenant platforms with role-based access, audit trails, and vendor management workflows
• Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines
• Familiarity with LLM training, fine-tuning, or evaluation workflows
• Experience with async Python (Trio, asyncio) or high-throughput API design
• Background in dashboards, monitoring, or observability tooling
• Experience working directly with external vendors or partners on technical integrations
• A background that isn't a straight line , e.g. math or physics into SWE, competitive programming, research into engineering, or a side project that outgrew its scope

Representative Projects:

• Building a unified platform for human data collection that integrates labeling workflows, vendor management, and QA for complex agentic tasks
• Developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation
• Creating evaluation and observability dashboards that catch reward hacks, measure environment difficulty, and give real-time feedback during production training
• Building environment quality review workflows that let researchers browse, grade, and provide feedback on training environments
• Developing automated environment quality pipelines that validate correctness and difficulty calibration before environments hit production training
• Building internal tools for browsing and analyzing training run results, environment statistics, and data collection progress

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Zuma is pioneering the future of agentic AI and our focus is to transform the rental market experience for consumers and property managers alike. Our innovative platform is engineered from the ground up to boost operations efficiency and enhance support capabilities for property management business across the US and Canada, a ~$200B market.

Off the back of our Series-A in early 2024, Zuma is scaling rapidly. Achieving our vision requires a team of passionate, innovative individuals eager to leverage technology to redefine customer-business interactions. We're on the hunt for exceptional talent ready to join our mission and contribute to building a groundbreaking technology that reshapes how businesses engage with customers.

As a Staff Engineer, you will:

Help define how humans collaborate with intelligent systems in one of the largest and most underserved industries in the world: property management. You’ll shape the technical foundation of a platform that is not just supporting human workflows, but executing them autonomously through AI agents. This is a rare opportunity to influence how an entire industry evolves, building tools that transform repetitive operational tasks into seamless, intelligent experiences.

Your work will directly contribute to how trust is built between humans and machines, how operations scale without added headcount, and how residents and staff experience a new, AI-powered standard of service. We’re not just building software we’re designing AI that people want to work with. Delightful, trustworthy, and deeply effective.

Join us to help lead the AI revolution in multifamily, drive meaningful real-world impact, and be part of reimagining what work can feel like when done side-by-side with intelligent agents.

You will be a cornerstone of our engineering organization, reporting to the VPE. This is a pivotal role where you'll lead critical system rewrites, architect scalable foundations for our AI platform, and establish the technical standards that will shape our engineering culture for years to come.

You'll work at the intersection of cutting-edge LLM technology and practical business applications, creating sophisticated systems that power our AI leasing agent while building self-serve experiences that enable rapid customer onboarding.

As our first US-based engineer, you'll bridge the gap between our product vision and technical implementation. This role offers a rare opportunity to directly influence how we architect the next generation of our platform.

You'll tackle projects like rebuilding our onboarding/configuration system to be self-serve, creating robust analytics infrastructure to measure AI performance, and reimagining our integration framework to connect seamlessly with customer systems.

Your work will significantly reduce manual engineering overhead while enabling rapid scaling of our customer base.

We're looking for a Staff Engineer to help us bring that future to life. This is not just another dev role. You'll be hands-on shaping the technical DNA of Zuma. You'll architect critical systems, tame legacy code, build net-new AI-powered experiences, and lay down the patterns future engineers will inherit.

If you're obsessed with building real products people use, especially products powered by LLMs, this might be your playground.

Why This Could Be Your Dream Role

• You'll work directly with cutting-edge LLM technology in a real-world application
• You want to work at a company where customers feel your impact every day
• You'll architect AI-powered systems that are transforming the real estate industry
• You'll have autonomy to design and implement innovative technical solutions
• Your work will directly impact thousands of apartment communities and millions of renters
• You'll receive significant equity in a venture-backed company with strong traction
• As we scale, your role and influence will grow with the company

Why You Might Want to Think Twice

• This is a demanding role that will often require extended hours and deep commitment
• As a founding team member, you'll need to wear multiple hats and step outside your comfort zone
• You'll need to make thoughtful tradeoffs between innovation and immediate needs
• You'll interact directly with customers to understand their needs and occasionally travel to their offices
• We're a startup - priorities can shift rapidly as we respond to market opportunities and customer needs
• If you're not comfortable getting your hands dirty with legacy code or speaking directly with customers, this isn't the job for you

Responsibilities

• Lead critical system rewrites to transform our architecture into a highly scalable, resilient foundation
• Own the design and performance optimization of our data storage systems, ensuring they scale with customer and AI demands
• Build and evolve our deployment pipelines, enabling reliable, automated releases for AI-first products
• Set up and manage modern cloud infrastructure from scratch, leveraging Infrastructure as Code (IaC) to ensure consistency, security, and scalability
• Establish engineering best practices, including observability, incident response processes, and system hardening for an AI-first platform
• Drive robust analytics and monitoring to track performance, reliability, and the effectiveness of our AI solutions
• Mentor engineers and elevate the team's capabilities across infrastructure, scalability, and AI product development

Your Experience Looks Like

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• 5+ years of experience building production-grade software systems, with a focus on scalability, performance, and reliability
• Proven expertise in backend development with Node.js, including API design, system architecture, and cloud-based services
• Experience with cloud infrastructure (AWS, GCP, or similar) and deploying production systems using Infrastructure as Code (e.g., Terraform, Pulumi)
• Hands-on experience with database design, performance tuning, and scaling high-throughput data systems
• Familiarity with building and maintaining CI/CD pipelines, automated testing, and modern DevOps practices
• Strong communication skills and ability to work effectively in a distributed, fast-paced environment
• Comfortable operating in early-stage, high-ownership environments with evolving requirements
• Bonus: Experience with React and TypeScript on the frontend, though this role leans backend/infrastructure
• Bonus: Exposure to LLM-based systems, AI infrastructure, or agentic AI workflows

Guiding Principles

• Customer‑First Outcomes

Every commit should trace back to resident or operator value. Whether it’s a new feature, infra investment, or AI capability, if it doesn’t solve a real problem, it doesn’t ship.

• Bias for Simplicity

We favor composable primitives over clever abstractions. Open standards, clean APIs, and clear contracts win over custom complexity, even if the custom version is cooler.

• Quality Is a Gate, Not an After‑Thought

Quality is built-in from day one. Our definition of done includes: test coverage, performance checks, basic observability, and internal docs. Shipping fast doesn’t mean skipping craftsmanship.

• Data‑Driven Choices

We use data to guide, not paralyze, our decision-making. We track leading indicators (cycle time, defect rate, NPS) and lagging signals (retention, revenue impact). We keep instrumentation lightweight but meaningful signal over spreadsheet.

• Transparency & Written Culture

Good ideas don’t expire in Zoom. We operate in public i

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You'll help property managers succeed with our AI platform while also driving continuous improvements in our internal tools and processes.

Responsibilities: Lead critical system rewrites to transform our architecture into a highly scalable, resilient foundation Own the design and performance optimization of our data storage systems, ensuring they scale with customer and AI demands Build and evolve our deployment pipelines, enabling reliable, automated releases for AI-first products Set up and manage modern cloud infrastructure from scratch, leveraging Infrastructure as Code (IaC) to ensure consistency, security, and scalability Establish engineering best practices, including observability, incident response processes, and system hardening for an AI-first platform Drive robust analytics and monitoring to track performance, reliability, and the effectiveness of our AI solutions Mentor engineers and elevate the team's capabilities across infrastructure, scalability, and AI product development

Your Experience Looks Like: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field 3+ years of experience building production-grade software systems, with a focus on scalability, performance, and reliability Proven expertise in backend development with Node.js, including API design, system architecture, and cloud-based services Experience with cloud infrastructure (AWS, GCP, or similar) and deploying production systems using Infrastructure as Code (e.g., Terraform, Pulumi) Hands-on experience with database design, performance tuning, and scaling high-throughput data systems Familiarity with building and maintaining CI/CD pipelines, automated testing, and modern DevOps practices Strong communication skills and ability to work effectively in a distributed, fast-paced environment Comfortable operating in early-stage, high-ownership environments with evolving requirements Bonus: Experience with React and TypeScript on the frontend, though this role leans backend/infrastructure Bonus: Exposure to LLM-based systems, AI infrastructure, or agentic AI workflows

Guiding Principles: Customer‑First Outcomes Bias for Simplicity Quality Is a Gate, Not an After‑Thought Data‑Driven Choices Transparency & Written Culture

Other Benefits: Great health insurance, dental, and vision Gym and workspace stipends Computer and workspace enhancements Unlimited PTO Opportunity to play a critical role in building the foundations of the company and Engineering culture

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Core Responsibilities: Define block-based build strategies explicitly compatible with facility geometry and crane systems Establish block size, weight, and envelope targets that optimize throughput and flow Translate vessel class, annual build rate, and steel tonnage into facility capacity requirements Define pre-outfitting rules that maximize upstream labor and minimize shipboard work Identify and eliminate facility-driven throughput bottlenecks early in design Ensure material flow supports parallel workstreams and predictable sequencing Integrate build strategy across facilities, heavy lift, manufacturing engineering, and design teams

Required Experience & Skills: Experience in block-based ship construction or heavy modular fabrication environments Strong understanding of crane-driven production systems and facility constraints Demonstrated throughput and production-flow mindset Ability to work early with incomplete information to shape irreversible facility decisions Comfort operating at the interface of design, facilities, and operations

Preferred Background: Experience influencing shipyard layouts, crane strategies, or major facility decisions Background in shipbuilding and facility layout design Experience in 3D modeling work flows

Benefits: Medical Insurance: Comprehensive health insurance plans covering a range of services Dental and Vision Insurance: Coverage for routine dental check-ups, orthodontics, and vision care Saronic pays 100% of the premium for employees and 80% for dependents Time Off: Generous PTO and Holidays Parental Leave: Paid maternity and paternity leave to support new parents Competitive Salary: Industry-standard salaries with opportunities for performance-based bonuses Retirement Plan: 401(k) plan Stock Options: Equity options to give employees a stake in the company’s success Life and Disability Insurance: Basic life insurance and short- and long-term disability coverage Additional Perks: Free lunch benefit and unlimited free drinks and snacks in the office

Additional Information: This role requires access to export-controlled information or items that require “U.S. Person” status.

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This is a senior, architect-level SME role responsible for supporting the definition of how ships are built and ensuring that facilities, equipment, automation, and operations are structurally aligned to a throughput-driven production system.

Key responsibilities include defining shipyard build strategies by vessel class, reviewing facility layouts and spatial design, integrating manufacturing engineering principles into facility and process design, and advising on major equipment and crane selection strategies.

The ideal candidate will have 10+ years of experience across shipyard facilities, manufacturing engineering, and operations, with demonstrated experience designing or transforming shipyard facilities.

Benefits include comprehensive health insurance, generous PTO and holidays, paid parental leave, competitive salary, and equity options.

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You will be a foundational technical owner of our Serverless product as it scales to thousands of enterprise customers, with real responsibility, autonomy, and impact. This is a chance to help build a new product vertical from the ground up inside a company that is already scaling at rocket-ship speed.

Your responsibilities will include:

• Building and maintaining core Serverless UI features (dashboards, logs, observability, configuration, usage)
• Designing and implementing backend APIs that power the Serverless product experience
• Improving performance, reliability, and scalability of customer-facing systems
• Working closely with Infrastructure to ensure product features align with platform capabilities
• Owning features end-to-end, from design through production and iteration

We're looking for a strong experience working across both frontend and backend, proficiency with TypeScript, Python, Postgres, and Next.js, and experience owning features end-to-end in production systems. Ability to context switch between UI, backend, and performance work, product-minded engineer who values clean abstractions and long-term maintainability, comfortable working in a fast-moving, low-process environment.

Nice to have experience building developer platforms or infrastructure-adjacent products, familiarity with observability tooling (logging, metrics, tracing) in production environments, background in distributed systems, container orchestration, or cloud-native architectures, experience with real-time systems, streaming logs, or high-throughput data pipelines, exposure to technologies such as Kubernetes, Prometheus, Datadog, gRPC, or similar systems, entrepreneurial mindset and strong ownership mentality.

We offer interesting and challenging work, competitive salary and equity, a lot of learning and growth opportunities, visa sponsorship and relocation assistance, health, dental, and vision insurance, regular team events and offsite.

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Privy is a developer tooling company that empowers users to take control of their online presence. We're looking for an experienced Engineering Manager to lead and grow a team of Infrastructure engineers.

Responsibilities

• Lead and grow a high-performing team of Infrastructure engineers
• Drive the future vision of infrastructure alongside talented infrastructure engineers
• Hold the team accountable to excellence in quality, throughput, and performance
• Ensure the team is working on the right scope of work and projects, align decisions with business impact
• Fill gaps as a player-coach; review PRs, write and review design docs, investigate incidents
• Coach engineers towards growth and their career goals

Benefits

• Competitive salary and benefits package
• Opportunity to work with a talented team of engineers
• Collaborative and dynamic work environment

Requirements

• Deep ownership and a high-level perspective on driving overall business impact
• Performance-oriented mindset, with a high bar for quality and excellence
• Technical excellence to be able to independently evaluate quality and technical feedback
• High emotional maturity, insightfulness, and care
• Strong past experience as a manager and leader

Preferred Qualifications

• Experience with designing and operating systems supporting hundreds of millions of users
• Secure enclave platforms, like AWS Nitro Enclaves
• Observability, incident response, capacity planning, performance tuning, and infrastructure automation (IaC, CI/CD for infra)
• Background in building low-latency, high-throughput systems for trading or payment processing
• Any blend of public cloud/BYOC architectures

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We believe that the foundation of every successful business lies in having the right people with the right skills. That is where we come in—helping Farmers build a winning team that delivers consistent and sustainable results.

This role develops, manages and maintains Client Group SLAs with our IT vendors. It assembles the MSLA components into appropriate customer facing services. Also produces regular reports to assess actual performance /availability of IT services against SLAs and reviews performance with key contacts.

Responsibilities

Develops and maintains customer facing SLAs regarding IT Services, working with various entities (Finance, Supplier, Business), as required

Understands charging principles and explains detailed costs to the business throughput measures, produces reports to assess actual performance and availability of services against SLAs, and reviews results with key contacts

Ensures the local SLA is kept up to date to meet changing requirements, understands the customer impact of new developments, and engages appropriate suppliers to meet the business needs; Conducts surveys, analyses customer satisfaction results, and initiates appropriate improvement programs

Understands any business variation in operational demand and engages appropriate suppliers to meet business needs

Engages with Program Managers to understand the customer impact of new developments and makes changes to SLAs as appropriate Produces the Service Agreements between legal entities, working with Finance, Legal and suppliers

Explains detailed charges/costs to the business and understands charging principles Understands and implements business throughput measures Mentors/coaches lower-level staff

Requirements

4-6 years of experience in a similar role

BS in Computer Science or similar

Previous experience in Finance / Insurance / Healthcare / or Regulated industries (PLUS)

Full English Fluency

Experience in the IT Vendor in IT Role Area

Internal Expense Report systems

Soft Skills

Planning and attention to detail

Negotiation & Communication

Influence and driving conversation

Technical Experience

Quickbase (Desirable)

Power Apps (Desirable)

MS Office

Service Now (Desirable)

Power BI (Desirable)

Benefits

This position comes with a competitive compensation and benefits package.

A competitive salary and performance-based bonuses.

Comprehensive benefits package.

Flexible work arrangements (remote and/or office-based).

You will also enjoy a dynamic and inclusive work culture within a globally renowned group.

Private Health Insurance.

Paid Time Off.

Training & Development opportunities in partnership with renowned companies.

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Responsibilities:

Pioneer research and stay up-to-date with the latest advancements in AIGC and VLM, applying SOTA technologies and frameworks to enhance the quality and performance of ad content generation.

Optimize and scale high-performance, large-volume systems to reliably handle massive datasets and ensure high throughput.

Lead the data collection, model training, evaluation, and deployment of advanced image processing and generation algorithms.

Analyse system performance and identify opportunities based on data analysis and online experiments.

Collaborate effectively with cross-functional teams (e.g., product manager, engineering, research) to deliver high-quality, end-to-end solutions.

Qualifications:

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.

4+ years of industry experience with a focus on computer vision, image/video generation and editing.

Demonstrated leadership or significant contributions to the design, data, training of advanced AIGC models (e.g. diffusion/AR models and distillation, VAEs etc.).

Excellent design and problem-solving skills, with a proven ability to translate ambiguous problems into clear, implementable solutions.

Proactive communication skills, with the ability to collaborate effectively across algo, product, and engineer teams.

Preferred Qualifications:

Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

5+ years of industry experience with a focus on computer vision, image/video generation and editing.

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Replit is seeking a skilled Software Engineer to join our team. As a Software Engineer at Replit, you will design and develop collaborative software applications that enable humans and AI agents to work together on shared shells, filesystems, and state.

Responsibilities:

• Design a collaborative 'Multiplayer Computer' that lets humans and AI agents work together on shared shells, filesystems, and state—conflict-free and in real time
• Build high-throughput backend applications and services
• Create tooling that helps AI systems minimize mistakes through static analysis and deterministic techniques
• Develop infrastructure (frontend & backend) that empowers product engineers to rapidly ship delightful user experiences
• Support sophisticated user interfaces, including terminals, code editors, window-management systems, and innovative experiences that require both creativity and algorithmic skill

Requirements:

• Bachelor of Computer Science or equivalent and 4 years of experience as a Software Engineer
• Must also possess 2 years experience building frontend; 2 years experience building backend; 2 years experience in at least one of the following: Developing rich and complex browser-based applications, Building high-throughput and novel backend services, Creating frontend infrastructure used by 100+ engineers, or Shipping your own products and engaging directly with users
• 2 years of experience with Typescript; Must be able to successfully complete competency-based interviews

Benefits:

• Competitive Salary & Equity
• 401(k) Program with a 4% match
• Health, Dental, Vision and Life Insurance
• Short Term and Long Term Disability
• Paid Parental, Medical, Caregiver Leave
• Commuter Benefits
• Monthly Wellness Stipend
• Autonomous Work Environment
• In Office Set-Up Reimbursement
• Flexible Time Off (FTO) + Holidays
• Quarterly Team Gatherings
• In Office Amenities

Want to learn more about what we are up to?

• Meet the Replit Agent
• Replit: Make an app for that
• Replit Blog
• Amjad TED Talk

Interviewing + Culture at Replit

• Operating Principles
• Reasons not to work at Replit

To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

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We are seeking Senior Infrastructure Engineers who are passionate about building and maintaining resilient systems at scale. Your mission will be to proactively find and analyse reliability problems across our stack, then design and implement software and systems to address them. You will build robust monitoring solutions, automate operational tasks, and continuously improve our infrastructure's reliability.

You Will:

• Drive Automation and Infrastructure as Code: Build and improve automation to eliminate toil and operational work. Maintain CI/CD pipelines and infrastructure automation using tools like Terraform or Pulumi. Create self-healing systems that can automatically respond to common failure scenarios.
• Optimise Performance and Infrastructure: Collaborate with core infrastructure and product teams to performance tune and optimise our cloud deployments (Kubernetes, Docker, GCP). Identify and resolve performance bottlenecks and implement capacity planning strategies.
• Elevate Developer Experience: Design and implement improvements to our build, test, and deployment systems to make software delivery faster, safer, and more reliable for all engineers.
• Drive Cross-Team Improvements: Partner with service owners across Replit to understand their pain points, and collaborate on implementing build/test/deploy enhancements within their specific services.
• Build Shared Tooling: Create and maintain centralized tooling and automation that improves the engineering lifecycle, from local development to production monitoring.
• Debug and Harden Systems: Dive deep into debugging difficult technical problems, making our systems and products more robust, operable, and easier to diagnose.
• Collaborate on Design Reviews: Participate in feature and system design reviews, contributing expertise on security, scale, and operational considerations.
• Build and Integrate: Write high-quality, well-tested code to meet the needs of your customers, including building pipelines to integrate with 3rd party vendors.

Required Skills and Experience:

• 4+ years of experience in Site Reliability Engineering or similar roles (DevOps, Systems Engineering, Infrastructure Engineering).
• Strong programming skills in languages like Python or Go.
• You write high-quality, well-tested code.
• Solid understanding of distributed systems. You've built, scaled, and maintained production services and understand service-oriented architecture.
• Experience with container orchestration platforms (Kubernetes) and cloud-native technologies.
• Experience implementing and maintaining monitoring/observability solutions, with strong skills in debugging and performance tuning.
• Strong incident management skills with experience participating in incident response and demonstrated critical thinking under pressure.
• Experience with infrastructure as code (e.g., Terraform) and configuration management tools.
• Excellent written and verbal communication skills, with an ability to explain technical concepts clearly.
• A willingness to dive into understanding, debugging, and improving any layer of the stack.
• You're passionate about making software creation accessible and empowering the next generation of builders.

Bonus Points:

• Experience with Google Cloud Platform (GCP) services and tools.
• Knowledge of modern observability platforms (Prometheus, Grafana, Datadog, etc.).
• Experience building reliable systems capable of handling high throughput and low latency.
• Experience with Go and Terraform.
• Familiarity with working in rapid-growth environments.

_This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday._

Full-Time Employee Benefits Include:

• Competitive Salary & Equity
• 401(k) Program with a 4% match
• Health, Dental, Vision and Life Insurance
• Short Term and Long Term Disability
• Paid Parental, Medical, Caregiver Leave
• Commuter Benefits
• Monthly Wellness Stipend
• Autonomous Work Environment
• In Office Set-Up Reimbursement
• Flexible Time Off (FTO) + Holidays
• Quarterly Team Gatherings
• In Office Amenities

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AI Deployment Engineer, Gov

Location

Washington, DC

Employment Type

Full time

Location Type

Hybrid

Department

OpenAI for Gov

Compensation

• Remote- Zone A$137K – $250.2K • 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 AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As the founding AI Deployment Engineer in the Public Sector segment, you’ll help government agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology.

About the Role

We are looking for a solutions-oriented technical leader to partner with our public sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies (federal, state, and local), policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You’ll then partner with their technical teams, subject matter experts, systems integrators, and implementation partners to move from prototype through production. You’ll take a holistic view of their needs and design an architecture using the OpenAI API and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Global Affairs, Applied Research, and Product teams.

This role is based in Washington, DC. We offer relocation support to new employees.

In this role, you will:

• Deeply embed with our most sophisticated public sector customers as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API.

• Work with senior customer stakeholders to identify the best applications of GenAI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap.

• Intervene directly to accelerate customer time to value through building hands-on prototypes and/or by delivering impactful strategic guidance, often in collaboration with systems integrators and implementation partners.

• Forge and manage relationships with our customers’ and implementation partners’ leadership and stakeholders to ensure the successful deployment and scale of their applications.

• Contribute to our open-source developer and enterprise resources.

• Scale the AI Deployment Engineering function through sharing knowledge, codifying best practices, and publishing notebooks to our internal and external repositories.

• Validate, synthesize, and deliver high-signal feedback to the Product, Engineering, and Research teams.

You’ll thrive in this role if you:

• Bring 7+ years of technical consulting (or equivalent) experience with public sector customers (U.S. federal preferred), bridging technical teams and senior stakeholders.

• Active TS/SCI clearance

• Have successfully led GenAI or traditional ML implementations for government agencies in close collaboration with systems integrators and implementation partners.

• Understand network and cloud architecture, including experience with on-premise deployments.

• Are an effective and polished communicator who can translate business and technical topics to all audiences.

• Have industry experience in programming languages like Python or Javascript.

• Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done.

• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.

• Are an effective, high throughput operator who can drive multiple concurrent projects and prioritize ruthlessly.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

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Sydney, Australia

Employment Type

Full time

Location Type

Hybrid

Department

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer, you’ll help the largest companies transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models.

About the Role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with GenAI. You will pair with senior customer leaders to establish a GenAI strategy and identify the highest value applications. You’ll then partner with their technical teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using ChatGPT, OpenAI API, and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Head of Technical Success, APAC.

This role is based in Sydney, Australia. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees

In this role, you will:

• Deeply embed with our most strategic platform customers as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API.
• Work with senior customer stakeholders to identify the best applications of GenAI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap.
• Intervene directly to accelerate customer time to value through building hands-on prototypes and/or by delivering impactful strategic guidance.
• Forge and manage relationships with our customers’ leadership and stakeholders to ensure the successful deployment and scale of their applications.
• Contribute to our open-source developer and enterprise resources.
• Scale the Solutions Architect function through sharing knowledge, codifying best practices, and publishing notebooks to our internal and external repositories.
• Validate, synthesize, and deliver high-signal feedback to the Product and Research teams.

You’ll thrive in this role if you:

• Have 6+ years of technical consulting (or equivalent) experience, bridging technical teams and senior business stakeholders.
• Are an effective and polished communicator who can translate business and technical topics to all audiences.
• Have led complex implementations of Generative AI/traditional ML solutions and have knowledge of network/cloud architecture.
• Have industry experience in programming languages like Python or Javascript.
• Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done.
• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.
• Are an effective, high throughput operator who can drive multiple concurrent projects and prioritize ruthlessly.

About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

San Francisco

Employment Type

Full time

Department

Consumer Products

Compensation

• $293K – $325K • 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.

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available.

About the Team:

We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch.

About the Role:

We’re seeking a Systems Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems.

In this role, you will:

• Design, implement, and debug system‑level components and services across kernel and user space.

• Configure and maintain OS platform services (init, services, networking, security policies) and related tooling.

• Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety.

• Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage.

• Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics.

• Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features.

• Establish strong engineering practices: code review, CI, reproducible builds, and release management.

• Partner with external suppliers to support builds and deployments.

You might thrive in this role if you:

• Have shipped production systems software on modern operating systems.

• Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management).

• Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries.

• Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs.

• Are fluent in user‑space foundations (service management, IPC, networking, packaging, automation).

• Have experience building platform images and designing update mechanisms for reliability and security.

Preferred Qualifications:

• Exposure to platform security (secure boot, sandboxing, mandatory access controls, attestation).

• Experience with graphics/media, hardware acceleration, or high‑throughput data paths.

• Familiarity with connectivity stacks and network configuration.

• Observability and diagnostics in distributed or resource‑constrained environments.

• Work on open‑source platforms or contributions to systems projects.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Microsoft AI are looking for a talented Principal Software Engineer at their Vancouver office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Principal Software Engineer, you will be responsible for designing and developing scalable backend systems, making key architectural decisions, and collaborating with multiple teams to deliver impactful solutions. You will contribute to shopping features in Copilot, Bing, and Edge browser, working closely with Product Management and Design teams. Your primary focus will be on building robust, long-lasting solutions that meet the needs of our customers.

Accountabilities

• Partners with appropriate stakeholders to determine user requirements for a set of scenarios.
• Leads identification of dependencies and the development of design documents for a product, application, service, or platform.

The Candidate we're looking for

Experience:

• 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Proficiency in designing and scaling high-throughput distributed systems and robust data pipelines.

Personal attributes:

• Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.

Benefits

• Competitive salary range of CAD $142,400 – CAD $257,500 per year.
• Opportunity to work on cutting-edge AI technology.
• Collaborative and dynamic work environment.

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What you'll do

You will join the Synopsys IP Group, a highly collaborative and innovative team focused on developing leading-edge interface IP solutions for memory technologies.

• Developing detailed verification testplans and comprehensive functional coverage models for complex memory interface IP.
• Implementing scalable UVM testbench infrastructure and designing robust test cases to verify training firmware functionality on RTL PHY models.

What you need

• Proficiency in SystemVerilog and UVM, with hands-on experience using simulation and waveform debugging tools.
• Strong background in developing verification solutions focused on productivity, performance, and throughput.

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What you'll do

• You will work with cross-functional teams including Content Management & Delivery, Messaging, Segmentation, Recommendation, and Experimentation to streamline the live services workflow.
• You will evaluate where and how EA's live service solutions, studio tech stacks, and vendor solutions can work together and help to achieve both engineering and business goals in an efficient and cost-effective manner.

What you need

• Bachelor/Master’s degree in Computer Science/related field or relevant experience.

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What you'll do

• You will work with cross-functional teams including Content Management & Delivery, Messaging, Segmentation, Recommendation, and Experimentation to streamline the live services workflow.
• You will evaluate where and how EA's live service solutions, studio tech stacks, and vendor solutions can work together and help to achieve both engineering and business goals in an efficient and cost-effective manner.

What you need

• Bachelor/Master’s degree in Computer Science/related field or relevant experience.

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