Machine Learning Engineer Radar Jobs

About the Job Lead performance work that turns large-scale AI workloads into faster, more efficient systems. As a Staff AI Performance Engineer, you will analyze and optimize AI training and inference workloads across distributed systems. Your work will connect compute, memory, networking and software behavior. You will lead complex performance workstreams across hardware and software. You will find bottlenecks, validate improvements and turn performance evidence into practical engineering decisions. You will build benchmarks, profile demanding workloads and develop C++ and Python tools for analysis and optimization. Your recommendations will help teams improve efficiency, scalability and reliability. This role gives you broad technical scope across AI infrastructure at data center scale. It is based in Milpitas, California. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will lead investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to lead technically complex work and coordinate improvements across teams. · Familiarity with MLPerf, a

About the Job Set the performance direction behind large-scale AI systems built for real deployment. As a Principal AI Performance Engineer, you will define how Graphcore analyzes and optimizes AI training and inference workloads. Your work will shape decisions across hardware, software, networking and system architecture. You will lead the hardest performance investigations, from model behavior to multi-node scaling. You will turn profiling, benchmarking and modeling evidence into technical roadmaps and engineering priorities. You will set measurement standards, guide distributed communication strategy and review critical C++ and Python tools. Your judgment will help teams make better decisions when data is incomplete. This role gives you rare influence across AI infrastructure at data center scale. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work happens through evidence, technical ownership and direct cross-team influence. You will guide strategy, resolve complex tradeoffs and raise performance-engineering standards across the organization. Decisions are shaped by benchmarks, simulations, models and clear technical debate. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Deep experience profiling and optimizing AI, machine learning or high-performance computing workloads at scale. · Proven technical leadership across complex performance-engineering or system-architecture initiatives. · Expert C++ and Python skills, including reliable tools or performance-sensitive software. · Expert understanding of compute, memory, communication and scaling behavior in distributed systems. · Ability to define benchmarks, measurement practices or optimization sta

About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo

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. In this role, you will design, build, and deploy AI-powered systems that accelerate AI adoption across CLEAR’s internal workflows and customer-facing product experiences. This role will partner directly with Product, Engineering, Data, Security, Legal, Compliance, Operations, and business teams to identify high-impact AI opportunities, rapidly prototype solutions, and productionize reliable, secure, and measurable AI systems. You will own use cases end-to-end, from discovery and evaluation through launch, monitoring, and iteration. What you'll do: Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment Measure and communicate AI impact across adoption, quality, cost reduction, productivity, customer experience, and business outcomes How you’ll measure success: Number of high-impact internal and customer-facing AI use cases launched Adoption and measurable business

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! The Role As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This will involve designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of Snorkel’s tooling. Develop and implement state of the art AI systems such as retrieval-aug

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 Validation Product Engineer on High Bandwidth Memory (HBM) technology you will be tasked with developing next-generation HBM products. Product Engineers are a key interface between Design, Manufacturing, Test, and Quality internal departments as well as external customers. We take ownership of HBM products; starting at the Design phase, through initial bring-up, qualification, and into volume production. The seniority level offered will be based on a combination of experience and education. In HBM HIG or equivalent experience (High Bandwidth Memory, Heterogeneous Integration Group), we innovate and integrate end-to-end groundbreaking front-end and backend processes with groundbreaking design, debugging various tests, and qualification techniques to develop the lowest power per bit solutions to improve customer experience in the field of ML (Machine Learning) and AI. The success of a sophisticated product such as HBM relies vastly on vertical integration and the various engineering working in unison. To provide greater detail, our HBM technology pertains to stacking numbers of DRAM chips along with a logic chip within one package through an assembly technology called TSV (Through Silicon Via). This greatly increases the memory density in a package, while allowing very high-speed signal transmission. Furthermore, "high bandwidth"; is an outstanding memory design area where custom gate-level design and RTL style logic design are blended into the same product, and most of the DDR or LPDDR design is based on the gate-level design onl

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary: Every gigabyte Micron ship is trusted to hold someone's data for years, whether in a phone, a car, a data center or an AI cluster. The NAND Product Reliability Architecture (NRA) team defines how we prove that trust before a product is released. As a Staff Engineer in NAND Product Reliability Architecture team, you will own the reliability architecture for Micron's newest NAND products end-to-end: interpreting reliability requirements, architecting qualification and stress strategies, developing and integrating reliability algorithms and system features, and optimizing coverage, sampling and test time so that we qualify faster without compromising quality. This is a high-leverage, high-visibility role. Your architecture decisions directly influence qualification cycle time, product time to market and the reliability our customers experience in the field. In a market where being first to qualify is a competitive advantage, speed is a core expectation. You will work closely with Technology Development, System Architecture, Design Engineering, Product Engineering, Manufacturing and Quality, and you will be expected to influence across these teams. Main Responsibilities: Comprehend NAND reliability specifications

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. We are driving the future of semiconductor design and innovation through advanced CAD, EDA, and AI-enabled engineering solutions. Our team works on technologies that help accelerate the development of next-generation memory and storage products used around the world. If you enjoy solving complex technical challenges, collaborating across engineering disciplines, and shaping the tools that enable breakthrough products, you'll find meaningful work here. As a CAD Engineer, you will play a key role in developing, improving, and supporting design automation tools and workflows used across integrated circuit design, physical implementation, and verification. You'll work closely with design, process, and software engineering teams to enhance productivity, introduce new technologies, and help drive the adoption of AI and machine learning within engineering workflows. Responsibilities: Lead the development, evaluation, and enhancement of CAD and EDA tools, flows, and methodologies Drive large-scale technical projects and provide expertise within CAD, design automation, and verification domains Guide AI and machine learning integration across CAD workflows and engineering applications Collaborate with design and process engineering teams to improve design efficiency and tool effectiveness Deliver training, documentation, and technical support for new tools, processes, and methodologies Minimum Qualifications: Bachelor's degree in Computer Engineering

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 We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: The Baseten Inference Stack at NVIDIA Dynamo Day 2x faster inference with KV cache-aware routing How Baseten multi-cloud capacity management (MCM) unifies deployments RESPONSIBILITIES Build the infrastructure and orchestration systems that de

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 We're looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference. EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: Agentic Kernels in Production How we built the new fastest API for GLM-5.2 Live draft model training for speculative decoding Making Kimi K3 Tokenization 18x faster The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. Profile and optimize inference end to end, from

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Secures AI Team The Okta for AI Agents Team is building the future of digital identity management. The way companies are using agents and allowing them access is undergoing a fundamental shift, enabling teams to move fast while staying secure. Our North Star is clear: To get AI right, you have to get identity right. We are not just managing identities; we are building the industry's first Identity Security Fabric for the agentic era. As organizations rapidly deploy AI, these non-human entities are acting with access to critical tools, often bypassing traditional perimeters and creating a 'Shadow AI' crisis. Our mission is to move identity from a reactive gatekeeper to a unified control plane, transforming AI risk into business ROI. We are tackling this by implementing a comprehensive four-pillar maturity model: Discover, Onboard, Protect, and Govern. We are driving innovation by defining the standards for Agentic Identity—including pioneer work with securing AI Agents and support for protocols like MCP. You will be helping us build the infrastructure that allows enterprises to scale AI safely, ensuring every access decision—whether made by a human or an automated agent—is authenticated, authorized, and audited at scale. We are a diverse team of engineers, product managers, and designers who are bringing Okta’s expertise in identity to define the future of Agent Identity management, focusing on enablement while staying secure. About the role

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. At Micron, we are transforming how the world uses information to enrich life through innovative memory and storage solutions. The DRAM Thin Films Process Engineering team develops advanced materials and deposition processes that enable future memory scaling, improved device performance, and next-generation semiconductor technology. Our team works at the forefront of process development to support DRAM technologies that power artificial intelligence, cloud computing, and data-intensive applications. As a DRAM Thin Films Process Engineering Intern, you will work alongside experienced engineers on a high-impact summer project focused on semiconductor process development and optimization. This role provides hands-on experience with experimental design, process characterization, data analysis, and multi-functional collaboration. You will contribute to real engineering challenges and present your results to technical and leadership audiences at the conclusion of the internship. Responsibilities Research and develop innovative solutions that support next-generation memory technology and thin film process advancement. Develop, complete, and analyze experiments to improve thin films process performance, manufacturability, and product quality. Apply statistical analysis, data science techniques, and AI-enabled tools to identify process trends, optimize performance, and accelerate engineering decision-making. Partner with process, equipment, and integration engineering teams to solve complex technic

Job Title Internship: Generative AI Engineer Job Description Start date: November (we are flexible) Duration: at least 3 months (with the option to extend) Type: Internship, Non-Thesis Weekly presence: 40 hours (32 hours could be an option), at least 3x week on-site Location: Eindhoven HTC Job title: Internship: Generative AI Engineer We're seeking an intern with hands-on expertise in Machine Learning, Natural Language Processing and Generative AI to join our team. In this role, you will design and build innovative and ethically responsible Generative AI solutions that effectively address real-world problems, balancing technical feasibility with user needs and business impact. Working at the intersection of natural language processing and machine learning, you will contribute to developing AI solutions that directly impact patient outcomes and Philips' growth in the healthcare sector. Your role: Design, train, and evaluate NLP and LLM-based solutions for various use cases, including retrieval-augmented generation (RAG), information retrieval & search, chatbots, structured information extraction and named entity recognition, text generation, summarization, and more Clean, preprocess, and curate data for evaluation, fine-tuning, and training Work closely with stakeholders across the organization to understand business needs, formulate problems, and deliver data-driven insights Keep up the latest advancements in generative AI research and integrate new techniques into the development process You're the right fit if: You are studying towards your Bachelor or Master's degree in Computer Science, Electrical Engineering, or a related field You have at least one year of hands-on experience developing NLP and ML/DL so

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. About the role: Foundation AI builds the platforms, services, and infrastructure that enable machine learning and generative AI across Roblox. In this role, you’ll work across areas such as model training and inference, LLM services, Agent infrastructure, data systems, experimentation, evaluation, and developer tooling while learning how to build reliable systems at scale. You’ll design, code, test, launch, and operate production features, partnering with teams across product, research, data, infrastructure, safety, creator, engine, discovery, and economy. You will report to an Engineering Manager within Foundation AI organization. You will: Build platforms and services that power machine learning, generative AI and agentic platform and product experiences across Roblox. Explore emerging technologies, including ML frameworks, LLMs, agentic systems, distributed systems, and GPU infrastructure. Improve the speed, reliability, observability, and cost efficiency of AI development Contribute to systems operating at Roblox scale while balancing quality, latency, reliability, and responsible data use. You have: You have an undergraduate/graduate degree in computer science or equivalent experience

Job Details: Job Description: The Role and Impact As a Manufacturing Quality and Reliability Engineer, you will be instrumental in ensuring high-volume manufacturing ramps meet Intel's rigorous quality and reliability standards. On a day-to-day basis, you will evaluate materials, processes, and techniques used in production, conduct quality audits, and develop systems for early detection and containment of potential issues. Your work will directly enhance Intel's ability to deliver high-performing products while fostering a culture of continuous improvement across manufacturing operations. Business Group You will be joining Intel Foundry, a world-class manufacturing organization dedicated to driving innovation and excellence across Intel's operations. This team focuses on ensuring quality and reliability in product engineering, manufacturing, and supplier collaborations, contributing to Intel's broader mission of delivering cutting-edge technology solutions. By leveraging data-driven insights and advanced methodologies, the group plays a critical role in supporting Intel's leadership in semiconductor technology. Key Responsibilities - Drive manufacturing ramp qualifications to ensure processes and products meet quality and reliability standards. - Specify inspection and testing mechanisms to monitor product and production equipment compliance. - Conduct in-depth quality assessments and audits to identify improvement opportunities. - Lead initiatives to optimize cost, ramp, and production volume efforts while maintaining quality. - Collaborate with product engineering forums to recommend design or process improvements for enhanced reliability. - Develop proactive systems and capabilities for early detection and containment of discrepancies. - Manage ma