Machine Learning Engineer Radar Jobs

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role We are on the lookout for a Senior Java Developer to join our Elasticsearch team and drive our work on the Inference API in Elasticsearch. The Elasticsearch Inference API is the integration layer between Elasticsearch and external machine learning services including Elastic's own Elastic Inference Service (EIS), third-party providers (Anthropic, OpenAI, Cohere, Google), and self-hosted models. It powers features like semantic search, reranking, and generative AI across Elastic Cloud and in hosted environments. You'll maintain and develop the plugin framework and REST API with your work spanning protocol design, streaming, async execution, billing integration, and with a tight collaboration with the wider inference team and the Kibana team. What You Will Be Doing Build and maintain integrations with internal systems and external inference providers, including schema negotiation, streaming (SSE), and error normalisation Contribute to the inference plugin's internal architecture: task settings, chunking strategies, rate limiting, and provider-level configuration Review open source contributions to the codebase and work with third party engineers to ensure their contributions meet our technology standards Participate in on-call rotation for inference-related incidents Write thorough tests: unit tests using ESTestCase, YAML-based REST

At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale's product security needs are growing as we ship to larger and more demanding customers. We're looking for a Senior Product Security Engineer to own our secure software development lifecycle and to be engineering's partner on building security into the product. Reporting to the Head of Security, you will work in close partnership with engineering. This is a senior, high-ownership role. You will own and operate a scalable SSDL, partner with engineering on security features and secure design, review the security of existing systems and new initiatives, and own how we find, track, drive to resolution and report on vulnerabilities in what we ship. This role is based in India. In your first year, success looks like an SSDL that scales with engineering rather than gating it, security review embedded in how new initiatives ship, and accurate, on-demand vulnerability reporting backed by a working path to resolution. What You'll Do Own and operate a scalable secure software development lifecycle: threat modeling, security requirements, secure design practices, and scanning that engineering can readily adopt. Partner with engineering on security features and secure-by-design architecture, from early design through i

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. 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

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

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

Zoox made the world’s first purpose-built commercial robotaxi, combining advanced self-driving hardware and software. In order to ensure safe operation, low latency and consistent resource utilization are critical. The Planner Compute team is responsible for the performance of the largest single software component within the autonomy stack, the motion planner. The Planner Compute team is looking for an expert in GPU performance. You will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution. The scope for GPU usage ranges from machine learning inference to custom CUDA kernels written specifically for the motion planner. In this role, you will: Analyze performance metrics to identify GPU hotspots and optimizations Contribute to the adaptation of our current planner to multiple GPU architectures with different resources Optimize ML models for latency and GPU memory usage Support engineers within Planner as a subject matter expert on CUDA & GPU performance Qualifications BS in computer science or related field and 6+ years of experience. Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight. Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments. Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines). Bonus Qualifications GPU kernel development experience There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies onl

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