Reliability Engineer Iii in United States

Job Details: Job Description: Intel is looking for highly motivated individuals with strong technical background and capabilities to sustain, ramp, and transfer all technology nodes in Arizona. They will drive rapid continuous improvements in safety, quality, yield, reliability, cost, process stability/capability, and productivity while maintaining rigorous quality control. The role of a Process Integration and Yield Engineer is to deliver high-quality analytical insights that influences / directs the factory resources to minimize defects, control process parameters, and improve overall factory yields. All improvements and sustaining work is done in close collaboration and partnership with the process to improve the capability of the tools and processes. Responsibilities may include, but are not limited to: Performing detailed data analysis using various statistical/data mining tools to identify the root cause of defect and yield issues. Identifying exclusionary or baseline sources of defects or yield impacts and recommending/leading corrective actions/fixes. Lead/participate continuous improvement projects on products and processes for improved performance. Provide expertise on process flow segments. Lead/participate in multi-area problem solving teams to provide expertise to troubleshoot complex yield problems. The ideal candidate should exhibit the following behavioral traits: Solid analytical skills and a passion for data analysis and problem solving. Organizational skills with attention to detail. Excellent interpersonal skills with the ability to work with people at all levels. Communication and presentation skills to influence a wide variety of groups at all levels. Demonstrate excellent teamwork and leadership skills, demonstrated pro

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

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 The Principal Systems Engineer will serve as a Product Design Owner (PDO) responsible for technical owner for the design, risk and integration of infusion pump systems and/or projects, which combine electro-mechanical hardware, embedded software, and user interface components, as well as the interface with other related EM and/or digital products. This role drives operational excellence and predictable, consistent execution in our products, and design and risk integrity and may serve as Risk Owner on some projects. The engineer is accountable for product safety, performance, reliability, usability and regulatory compliance, as well as risk. The PDO drives design decisions, manages design control activities, may be accountable for a product risk file, and collaborates across engineering disciplines and cross-functions to deliver robust, reliable, safe and innovative infusion therapy solutions. What you will be doing: Leads interdisciplinary design and development of medical products in compliance with FDA, EU MDR,

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Role Summary: We are looking for a talented and detail-oriented Sr Data Engineer to tackle data challenges. You will design, build, and maintain critical data pipelines and datasets, supporting areas like recruiting, compensation, talent management, and learning and development. Your work will enhance data accessibility and empower the People Team and business leaders to make informed decisions with high-quality, reliable data. Key Responsibilities: Develop and maintain robust data pipelines and datasets. Build foundational data products for key business areas. Enhance self-service data capabilities for the People Team. Ensure high standards in ETL/ELT operations, data quality, and pipeline reliability. Join us to drive impactful change and support SoFi's mission of fostering a thriving workplace through data excellence. What you’ll do: Design and build production dbt models in Snowflake that integrate Workday and other People systems into well-modeled, documented datasets, including slowly changing dimensions for People history. Build and operate Airflow DAGs that ingest People systems data and orchestrate dbt runs, keeping loads reliable and re-runnable. Own data quality and observability: dbt tests, freshness checks, row-count validation, and monitoring so issues are caught before stakeholders see them.

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We’re searching for a highly motivated, technical leader to design, drive, and operationalize rack-scale factory and deployment flows for next-generation data center products. The ideal candidate will combine deep systems expertise, decisive technical leadership, and a passion for building reliable, debuggable, and scalable manufacturing and deployment solutions. What you’ll be doing: Lead and drive rack-scale/L11 flows for factory and initial data center deployment. Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations. Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp. Champion reliability, debuggability an

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Senior Software Engineers independently drive complex technical work, shape the systems and technical decisions within their teams, and enable other engineers to deliver high-quality, scalable solutions. Vanta's product monitors the security posture of thousands of companies, pulling tens of millions of API calls of data per day, pushing information from hundreds of thousands of laptop agents, and running tests against that data continuously to identify potential security threats. Our infrastructure and tooling need to stay ahead of exponential growth in our customer base. As a Senior Software Engineer at Vanta, you'll drive complex projects across our technical stack, contribute to the technical direction of your team, and mentor other engineers. Your past experience will be leveraged to enable and accelerate Vanta's growth. Visit our Vanta Engineering Blog to learn more about what our team is working on! Tests are at the heart of how Vanta continuously monitors security and compliance for our customers. The Test Core team builds the runtime platform that powers these checks. We own how Tests are scheduled and executed, how their results are persisted and exposed, and the systems that keep this runtime reliable as Vanta grows. In this role, you'll work on some of the core systems behind Vanta's Tests platform. You'll tackle problems around the reliability, correctness, and performance of Test execution, evolve the systems and abstractions that allow the platform to scale, and make it easier for other engineering teams to build on the Tests runtime. Many of these problems span multiple systems and teams and require a deep u

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

As a Senior Backend Engineer on Coder's Enterprise Experience team, you'll build the systems that help large organizations run Coder in production with confidence. You'll improve how Coder scales, how it's upgraded, and how reliably it performs in regulated, air-gapped, and enterprise environments. You'll work on a genuinely cross-functional team of backend, platform, and QA engineers who own the end-to-end experience for Coder operators. From designing new features to evolving Coder's architecture, you'll partner across engineering and product to solve complex problems and ship software that operators trust. What you'll do here Design and build new features end to end, from technical design through production rollout. Design and implement backend architecture changes that support Coder's long-term scalability goals. Investigate and resolve scalability bottlenecks under production-like load, from database access patterns to concurrency handling in coderd. Improve database migration safety and upgrade reliability through schema compatibility, background migrations, and safe rollback strategies. Own the backend side of issues surfaced by Coder operators and administrators. Document the design, implementation, and operational tradeoffs of the systems you build. Participate in code reviews, RFC-style design discussions, and on-call rotations for the services you own. What we're looking for 5+ years of professional software engineering experience, including significant production experience with Go. Deep understanding of Go's concurrency model, including goroutines, channels, the sync package, and debugging race conditions under real-world load. Experience designing and operating relational databases in production, including schema design, migrations, and transactions. Strong verbal and written communication skills. Exceptional debugging and troubleshooting skills, with the persistence to drive complex problems to resolution. A self-motivated, analytical engineer who enj

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse using open formats like Apache Iceberg — at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world's leading data platforms. We are hiring a Senior Software Engineer for Observe by Snowflake on the Data Management team. This team is responsible for the tables, views, and materialized views at the core of Observe's architecture. Observe's data lake approach lets customers correlate heterogeneous telemetry — logs, metrics, traces, events — across a unified data model. This role owns that data model: how customers define, shape, and query the semi-structured data that makes cross-si

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. Senior Software Engineer - External Observability Platform Location: Bellevue, WA (Hybrid: 3 days/week in-office) Team: Infrastructure & Observability Platform Engineering About the Role Snowflake’s Data Cloud processes exabytes of data across multi-cloud global environments every day. Delivering seamless reliability and real-time visibility to thousands of global enterprise customers requires an Observability Platform built on hyper-scalable backend distributed systems. We are seeking a Senior Software Engineer to own key components of our AI native External Observability Platform . In this role, you will contribute to the technical road map for customer-facing telemetry, system metrics, audit logs, distributed tracing, and actionable operational insights. You will build high-throughput, low-latency infrastructure capable of ingesting, processing, and serving petabytes of telemetry data with strict SLA guarantees. You will join a team of world-class engineers in our Bellevue, WA office. To be successful, you must be deeply technical, capable of leading complex technical projects, and skilled at collaborating with the brightest technical minds in the industry. Key Responsibilities Develop and Scale Distributed Infrastructure: Design and implement key components of Snowf

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. We are hiring a Senior Frontend Engineer, AI Products team at Observe by Snowflake. As an AI Product engineer you'll always be thinking first about the user experience and how to create the best product, technical choices, and implementation decisions that stem from that product first thinking. This team builds the AI-powered products and developer tooling at the core of Observe's platform, including our flagship AI SRE product, real-tim

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating deployments and monitoring systems to optimizing performance and managing incidents. We all work closely with our users, learning from their past struggles in operationalizing ML, onboarding them onto our platform, and turning our learnings into ideas for improving Baseten. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Build and maintain scalable infrastructure to support the deployment and operation of machine learning models. Establish standards and best practices for reliability and performance across the infrastructure. Automate processes when relevant, particularly for managing CI/CD pipelines. Own products and projects end-to-end, functioning as both an engineer and a project manager, with a focus on user empathy, project specification, and end-to-end execution. Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions. Mentor junior team members and contribute to knowledge sharing within the organization. Navigate ambiguity and exercise good judgment on tradeoffs and

What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity Most engineers spend their career making predictable systems faster. You'll spend yours making non-deterministic ones trustworthy. As a senior engineer on our AI product team, you'll architect the Campaign Builder and Agent experiences marketers and sellers open every day to go from idea to personalized assets in minutes. You'll partner directly with product, design, and the founders to define what an agent-first GTM platform should feel like, and your calls on architecture, evals, and guardrails compound across thousands of customer accounts. This role is in person in New York City, five days a week, and we ship weekly. What you'll own The core agent surfaces. Architect and ship the Campaign Builder and Agent experiences end-to-end. Frontend, backend, prompts, evals, the whole stack. Reliability on top of LLMs. Make non-deterministic models feel deterministic at the surface. Build the retries, fallbacks, and orchestration so the customer never sees the failure mode. Evals and guardrails. Define how we measure quality, catch regressions, and keep brand and tone consistent across thousands of customer accounts. Speed and feel. AI products live or die by latency and the loop between intent and output. You'll obsess over both, and use coding agents and agent networks to ship f