Performance And Systems Engineer Jobs

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 ship AI products. THE ROLE As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. 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 Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containerizati

About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data. In this role, you can expect to Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions, from approval and line assignment to loss forecasting Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards for model development, validation, and governance Help identify where AI/ML creates measurable impact for me

Job Requisition ID # 26WD101542 Position Overview Autodesk is looking for a skilled and innovative Senior Data Engineer to join our Compliance team, which builds data-driven systems to detect and address non-compliant usage of Autodesk software. This is a key strategic initiative that leverages large-scale data processing and analytics to drive business impact. In this role, you will design, build, and optimize scalable data pipelines and distributed processing systems that handle billions of records. You will focus on improving platform reliability, performance, scalability, and operational efficiency while enabling business-critical analytics. We are looking for an engineer who combines strong expertise in big data technologies with hands-on experience using AI-powered development tools to accelerate engineering workflows, improve code quality, and deliver solutions faster. The ideal candidate is technically strong, self-driven, comfortable owning complex engineering initiatives, and passionate about leveraging modern technologies and AI-assisted development practices to solve challenging data engineering problems. Our technology stack includes: Python, SQL, Apache Spark, PySpark, Spark SQL, Apache Airflow, Hive, Presto/Trino, Snowflake, AWS (S3, EMR, Glue), Git, Jenkins, Power BI, Looker, and AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or equivalent solutions. Responsibilities Leverage AI-powered development tools to accelerate coding, debugging, refactoring, test generation, documentation, and troubleshooting of complex data engineering solutions In

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Heterogeneous Integration Group (HIG) sits within the Technology and Products Group (TPG) and develops industry-leading High Bandwidth Memory (HBM) solutions for next-generation AI and high-performance computing systems. Micron is seeking an experienced MTS - HBM Thermal Integration Engineer to drive thermal performance optimization for next-generation High Bandwidth Memory products. This role sits at the intersection of thermal simulation, silicon characterization, process technology, package development, manufacturing, test engineering, and product integration. Key Responsibilities Drive thermal performance optimization across HBM products through design, process, packaging, assembly, and test improvements Develop and implement thermal learning plans, characterization strategies, and design-of-experiments (DOE) to accelerate technology understanding Analyze silicon characterization, inline metrology, manufacturing, and test data to identify key drivers of thermal behavior and variation Partner with thermal simulation teams to improve understanding and correlation between predictive models and measured silicon performance. Work closely with wafer fabrication, package development, assembly, product engineering, and reliability teams to resolve thermal challenges and enable product improvements. Identify and implement opportunities to reduce thermal resistance, improve thermal consistency, and enhance product performance. Drive cross-functional technical investigations and

Job Summary The Supplier Quality Engineer II is a fully proficient professional individual contributor responsible for ensuring that purchased electronic, electrical, electromechanical, and mechanical components, materials, assemblies, and supplier-provided services meet company, customer, regulatory, and contractual quality requirements. Working with limited supervision, this position independently manages routine to moderately complex supplier-quality assignments across supplier qualification, risk assessment, auditing, performance monitoring, nonconformance investigation, corrective and preventive action, change management, and continuous improvement. The (Supplier Quality Engineer II) partners with suppliers and internal stakeholders in Strategic Purchasing, Procurement, Engineering, Manufacturing, Quality, Product Management, Logistics, and other functions to resolve quality issues, strengthen supplier capability, reduce risk, and improve product and process performance. The role applies broad working knowledge of quality engineering principles, electronics-component manufacturing processes, drawings and specifications, quality systems, structured problem-solving methods, and statistical analysis to identify root causes, evaluate containment and corrective actions, and recommend practical solutions. Consistent with a second-level professional contributor role, the Supplier Quality Engineer II independently handles varied assignments within established policies and professional standards, exercises judgment when selecting and adapting methods, manages multiple priorities, and escalates issues that involve significant technical, commercial, customer, or compliance risk. The position may lead to defined supplier-quality projects, facilitate cross-functional problem-solving activities, and provide technical guidance or knowledge sharing to less-experienced employees without formal people-management responsibility. This is the second level within the Supplier Qualit

About the Team The ChatGPT Space team is building a shared workspace where people and AI agents turn ideas into polished, editable work. Space brings teammates, ChatGPT, and dots together around shared knowledge and projects, with creation experiences spanning Pages, Sheets, Slides, and new kinds of artifacts. We want work to keep improving beyond the first draft, using shared context and collaboration to stay current as projects evolve. We work across product, design, and research, partnering closely with model training teams to shape how frontier models create and edit artifacts. We ship quickly, learn from real usage, and hold a high bar for craft, correctness, and speed. About the Role We’re hiring a Frontend Software Engineer to build a top-tier collaboration experience and help shape how people work with AI. This is a craft-heavy role: you’ll partner closely with design to prototype, iterate, and polish new interaction models, then turn them into reliable, high-performance product experiences. You’ll help define what great looks like for collaboration between people and agents: how shared context is represented, how contributions and changes are made understandable, and how users stay oriented and in control as work moves between teammates and AI. What You’ll Do Build and ship polished, high-performance UI for Space and its collaborative workflows. Partner tightly with design to turn prototypes into production-quality experiences, from layout and typography to motion and interaction details. Develop intuitive interfaces for creating and editing shared content, organizing project context, and reviewing contributions from teammates and AI as work evolves. Own frontend architecture decisions across component systems, state management, navigation, and rendering performance. Improve quality and reliability through testing, instrumentation, accessibility, and thoughtful UX for loading, errors, and concurrent changes. Collaborate with research, platform, and backend

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Design Engineer at Micron Technology, Inc., you will be responsible for designing and analyzing digital and analog circuits used in the development of memory products. We are engaged in developing groundbreaking silicon-to-systems solutions – right from technology development and advanced memory designs to product development, systems design and validation resulting in world class memory solutions! In this position, you will collaborate with Micron’s various design and verification teams all over the world and support the efforts of groups such as Product Engineering, Test, Probe, Process Integration, Assembly and Marketing to proactively design products that optimize all manufacturing functions and assure the best cost, quality, reliability, time-to-market, and customer satisfaction! Job Description As a Staff DRAM Design Engineer, you’ll play a critical role in shaping memory architectures and circuit innovations that directly impact product performance, power, and reliability. This is a hands-on design role where your expertise will drive key decisions from concept through silicon validation, while collaborating with cross-functional teams to deliver meaningful results. Responsibilities: Lead design and optimization of DRAM circuits including memory array, control logic, datapath, and test logic Perform and analyze circuit simulations using tools such as SPICE and Verilog Evaluate architectural trade-offs impacting power, performance, and die size Integrate layout parasi

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a member of the Applied AI team at Anthropic, you will be an Applied AI Engineer supporting a dedicated national security mission program. You will be the customer's trusted technical advisor, working closely with their engineering and mission teams as they build and ship new capabilities powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding them through the most cutting-edge implementation patterns for LLMs. Working closely with our Sales, Product, and Engineering teams, you'll guide the customer from technical discovery through successful deployment, much of it on-site in secure environments. You'll combine deep engineering expertise and cyber domain knowledge with customer-facing skills to help the customer unlock the full potential of Claude and move their mission capabilities closer to the frontier, while maintaining our high standards for safety and reliability. Responsibilities Serve as a specialist technical advisor for one or more national security mission programs, from discovery and evaluation through deployment and adoption, coordinating internally across multiple teams to drive customer success Support the customer as they build with Claude Code, the Claude API, and Claude for Enterprise Partner with account executives and Applied AI Architects to translate mission requirements into technical solutions Influence technical architecture decisions and integration into the customer's existing stack by developing customized pilots, prototypes, and evaluation suites Help develop evaluation frameworks to measure Claude's performance for mission-specific use

We are seeking a Senior Staff Engineer to join our growing Gurugram Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Senior Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 15+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer sc

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! Senior Staff Backend Engineer About the Team We build enterprise software that helps organizations optimize sales performance, enabling go-to-market agility. Our engineering organization includes multiple product application teams responsible for delivering core customer-facing capabilities. We are seeking a Senior Staff Backend Engineer to join our application teams and help set technical direction across multiple domains within engineering. You'll work alongside staff, senior, and early-career engineers, and partner closely with engineering leadership to define, evolve, and scale the systems that power enterprise-grade product workflows. This is an opportunity to own complex, multi-domain technical problems and shape product direction beyond a single team. We are low on meetings, high on accountability. Most of the teams are in the EST time zone, but we have a few located in AST, PST, and Central as well. What you'll be doing You will play a pivotal role in shaping the technical direction of our application stack across multiple domains. You will lead development efforts for our most complex initiatives, the kind that span two or more teams or product areas, and serve as a technical benchmark for system design, code quality, and long-term maintainability. You'll operate at the intersection of data modelling, business logic, and enterprise-scale reliability, and your work will often set standards that neighboring teams adopt. This remains a hands-on

We are seeking a Senior Software Engineer to join our growing Bengaluru Products & Technology team to provide technical direction, direct architecture, and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Senior Software Engineer on this new team, you will be responsible for developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 5+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maintaining distributed

The Lead EMS/SCADA will be responsible for the design, development, integration, testing, and deployment of Energy Management Systems (EMS) and SCADA solutions for utility-scale Battery Energy Storage System (BESS) projects. The role will drive system architecture, control strategies, monitoring solutions, and communication interfaces to ensure optimal performance, reliability, and grid compliance. Source: Adani Group | Job ID: 58677

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role We are seeking a Senior AI Engineer to join our AI Platform team. The AI Platform team is focused on enabling and building disruptive, innovative solutions to transform the wealth technology landscape with AI across our product suite and is growing quickly. As a Senior AI Engineer, you will be responsible for architecting, leading, and driving the execution of the core AI capabilities that power our platform. This is a high-impact role for an engineer who thrives on the frontier of applied AI and maintains a relentless focus on shipping. You will not just work with LLMs and agentic frameworks; you will own the end-to-end delivery of AI-native products, ensuring that cutting-edge AI systems are hardened into robust, scalable, and high-performance production systems. Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role. What You’ll Do Drive the end-to-end execution and delivery of AI-native products, moving from initial prototype to scalable production services with high velocity Architect, build, and productionize core components of our AI platform – including: LLMs and the surrounding ecosystem (e.g., vector DBs, pr

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down. What you'll do: Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines. Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through. Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow. Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization. You may be a good fit if you: Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation. Have a strong foundation in distributed systems: replication, cons