Distributed Systems Engineer Data Platform Delivery Database Retrieval in United States

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Quality is our competitive advantage. Every member of our fully remote team is a maker at heart, caring deeply about the quality and feel of our work. While the industry optimizes for speed and metrics alone, we believe that craft and quality have lasting value. Quality creates gravity — it pulls people toward our team and product rather than requiring us to push. This philosophy drives everything we do, from product decisions to hiring choices. For this role, we expect robust design skills, sharp product thinking, and the ability to engage in technical discussions. We work in small, autonomous project teams, where engineers are paired tightly with designers to explore ideas, build prototypes, deploy internal builds, and ultimately ship to customers. You will be a key element of projects from beginning to end. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Own the experience of our iOS and Android mobile apps, including guiding the adaptation of desktop features to mobile Pair closely with mobile engineers and product leads to initiate and complete mo

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Quality is our competitive advantage. Every member of our fully remote team is a maker at heart, caring deeply about the quality and feel of our work. While the industry optimizes for speed and metrics alone, we believe that craft and quality have lasting value. Quality creates gravity — it pulls people toward our team and product rather than requiring us to push. This philosophy drives everything we do, from product decisions to hiring choices. For this role, we expect robust design skills, sharp product thinking, and the ability to engage in technical discussions. We work in small, autonomous project teams, where engineers are paired tightly with designers to explore ideas, build prototypes, deploy internal builds, and ultimately ship to customers. You will be a key element of projects from beginning to end. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Pair closely with engineering and product to initiate and complete roadmap projects, no hand-offs Spot opportunities to redesign or refine key screens and flows, as well as smaller quality issues an

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Senior Manager, Manufacturing Engineering owns the manufacturing engineering function across Hyliion's Cedar Park, TX headquarters and primary production site and its Milford, OH R&D operations. The role is the bridge between the engineering design of the KARNO Power Module and the scalable, repeatable production system required for commercial ramp, defining and driving the processes, tooling, documentation, and infrastructure that transform KARNO from a highly engineered prototype into a manufacturable product. This is a player-coach role: the incumbent builds and leads a team of manufacturing engineers while remaining personally hands-on in the most challenging production problems. AI at Hyliion At Hyliion, AI is core to how we work. We equip every team member with leading AI tools and count on you to use them — to move faster, solve harder problems, and help us realize the full potential of KARNO technology for the world. Duties and Responsibilities Productionization: translate engineering designs into manufacturable, repeatable, and scalable production configurations across both sites, aligned to the commercial ramp roadmap. Tooling and process development: design, develop, and qualify manufacturing tooling, fixtures, and processes that support quality, efficiency, and volume scalability. Manufacturing documentation: own PFMEAs, control plans, work instructions, SOPs, and MBOMs, keeping them accurate, current, and accessible to the production floor. Lean and material flow: define and implement standard work, material flow, and handling strategies that increase throughput, reduce waste, and prepare the factory for

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role As AI agents become more capable at software engineering, and automate more of our internal work, they could become a dangerous cyber threat. People in this role will help OpenAI prepare for security threats from advanced AI agent insiders. In this role, you will: Identify paths by which capable future internal AI agents could compromise OpenAI. Design security controls - focusing on measures with long lead times that benefit from advanced preparation. Stress-test defenses with AI agent evaluations and penetration tests You might thrive in this role if you: Are deeply technical across security and modern infrastructure, and are comfortable digging into the details of operating systems, cloud, containers, CI/CD, or distributed systems. Have strong software engineering skills and enjoy building prototypes yourself. Are interested in engaging with stakeholders and can do so effectively. Bonus: have experience securing cloud infrastructure, and are deeply familiar with core components of the AI stack. Compensation Range: $293K - $405K USD 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

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Health100 is America's trusted front door to health and care. The Health100 platform integrates any participating health plan, PBM, pharmacy (retail and specialty), provider, digital health point solution provider, and employer, and addresses the top health care challenges for the consumer. The Senior Manager, Software Engineering will lead engineering teams building a best-in-class consumer health experience on the Health100 platform, focused on identifying, prioritizing, shaping, and executing complex platform initiatives. As a key member of our engineering organization, you will drive innovation, manage cross-functional teams, and deliver scalable cloud-native and AI-enabled solutions that improve consumer experiences and business outcomes. This role works within a top-notch organization of software developers who identify, design, and deliver technology solutions using Java, distributed systems, cloud platforms, and AI-powered capabilities to achieve defined business value. You will guide the integration and validation of complex technology solutions, drive engineering excellence, and leverage emerging technologies including Generative AI and intelligent automation to accelerate innovation and efficiency *Remote eligible within the United States. Preference for candidates in close proximity to our Woonsocket, RI headquarters. Resp

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a strategically-minded, technology-focused, and customer-centric Engineering Manager to lead one of our Infrastructure teams here. You will lead a team responsible for building, operating, and scaling the cloud infrastructure and platform systems that underpin CLEAR’s services, ensuring reliability, performance, and security across our environments. A successful candidate brings strong experience in cloud infrastructure, distributed systems, and operational excellence, along with a solid foundation in software engineering. You are an effective communicator who can lead complex infrastructure initiatives from inception through delivery, and thrive in fast-paced environments. This role requires a focus on building resilient, scalable systems, driving automation, and leading and developing high-performing engineering teams. What you'll do: Hire, develop, and grow engineering talent through coaching, mentorship, performance management, and career development planning Set clear goals and expectations, provide regular feedback, and foster accountability across the team Own and execute the roadmap for cloud infrastructure and platform engineering, and reliability initiatives Design, build, and operate a scalable, secure, and highly available cloud platform infrastructure Drive automation across infrastructure provisioning, deployment, and operations to improve efficiency and reduce manual overhead Establish and enforce best practices for system reliability, observability, incident response, and disaster recovery Partner with eng

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Your Role at Baxter Provides enterprise-level technical leadership for cloud shared services and related connected-care ecosystems. Collaborates with engineering, product, and business leaders to shape long-term architectural strategy, establish technical standards, and guide the evolution of secure, cloud-native services that support multiple products, regions, and business domains. Serves as a senior technical leader for distributed systems, GraphQL and API architecture, multi-region cloud strategy, service interoperability, scalability, security, resiliency, observability, SOC 2 readiness, and operational excellence. Partners closely with executive leadership, product management, cybersecurity, quality, regulatory, operations, and engineering teams to align technology investments, architectural decisions, and platform capabilities with business objectives and sustained growth. <span style="color:

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This position may be a hybrid or fully remote position, as decided by your manager. If designated as hybrid, you’ll divide your time between working remotely from your home and an office location, so you should live within commuting distance. If designated as remote, you’ll be working remotely from your home and may occasionally visit a GoDaddy office to meet with your team for events or meetings. Your hiring manager can share more about this role’s hybrid or remote designation. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC. Join Our Team Join a team powering secure, scalable email services for millions of customers worldwide! As part of GoDaddy's Professional Email team, you'll solve complex challenges in distributed systems, cloud infrastructure, security, and AI while modernizing critical platforms that businesses rely on every day. If you enjoy owning impactful systems, working across a diverse technology stack, and building innovative solutions at scale, you'll feel right at home here. What you'll get to do... Design, build, and maintain highly available, scalable APIs and services used by millions of customers Deploy, manage, and optimize cloud infrastructure in AWS Architect and implement modern solutions that improve performance, reliability, and security Leverage AI technologies to enhance development workflows and create innovative customer experiences Monitor, troubleshoot, and resolve complex production issues using modern observability and monitoring tools Drive continuous improvement through automation, modernization, and operational excellence C

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. LEAD. STRATEGIZE. TRANSFORM. We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness. WHY THIS ROLE? This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways. WHAT YOU'LL DO: Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem. Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions. Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI. Mentor Level 3 architects on best practices for MLOps and architectural design. TECHNICAL DEPTH & RISK MANAGEMENT: Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP). Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle. Governance: Architect data security and access controls specifically for sensitive AI/ML training data. SNOWFLAKE-NATIVE TECH STACK: Snowflake Model Registry, Cortex Functions, Python,