Senior Software Engineer Machine Learning 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

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role The Sr Embedded Software Engineer - Radar & DSP will play a key role in developing advanced RF sensing capabilities for Mach’s autonomous defense platforms. You will be responsible for designing, implementing, and optimizing radar software across the full development lifecycle; from algorithm prototyping to embedded deployment. This role involves close collaboration with cross-functional teams to ensure high-performance, low-latency radar systems that meet mission-critical requirements. Success in this role requires strong technical execution, adaptability, and a hands-on approach in a fast-paced, iterative environment. Key Responsibilities Develop, test, and implement radar software for RF sensing technologies ensuring high performance and reliability. Build next generation counter UAV systems through hands on application of radar defense systems to defend human lives, critical infrastructure, and high value assets for the United States and its allies Design and implement efficient, well-tested code in C++, Python or C. Work closely with other engineers to ensure seamless hardware-software integration. Develop and maintain signal processing algorithms tailored for RF sensing systems, ensuring real-time performance and low-latency

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. Develop observability to track ML model lifecycles from data generation to on-road validation. Maintain an in-house ML inference platform to serv

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like quantization, distillation, and model compression. Work with autonomy engineers to optimize, validate, and deploy large language models. Develop and maintain a world-class model compiler framework, FTL . Write robust, high quality software to increase our confidence in our vehicle

Zoox is building fully autonomous vehicles designed from the ground up for robotaxi service — and as we scale toward launch, our engineering infrastructure has to scale with us. We're hiring a Staff Site Reliability Engineer to own source control at Zoox, serving as the technical lead for the platform that every engineer depends on daily. This is a hands-on lead role. You'll set the direction for our Git-based monorepo, drive a restructuring of our Source Code management strategy, build the tooling that improves reliability and developer workflows, and partner with platform, security, and product teams to make source control a strategic asset rather than a bottleneck. The ideal candidate leads by building — with deep expertise in monorepo management (branching strategies, code review workflows, access controls, CI/CD) and a track record of improving developer productivity through code, not just guidance. You take ownership, measure what matters, and have the technical credibility to make decisions stick. In this role, you will: Own the technical strategy and roadmap for source control at Zoox. Plan and execute a strategic effort to scale source code management at Zoox: scoping, design, implementation, cutover, and validation, in partnership with security, platform, and engineering teams. Build and operate monorepo scalability improvements across repo structure, branch strategy, code ownership, large-file handling, and CI integration — including the scripts, hooks, and automation that make them stick. Develop the guardrails and developer-facing tooling that reduce toil for SRE and product engineering alike, measured by build times, merge friction, and interrupt volume. Set the technical bar through code reviews, design proposals, and pairing — and serve as the hands-on authority for source control decisions across Zoox engineering Qualifications 5+ years operating GitH

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role As a Senior/Staff Software Engineer working on driving behavior verification, you are responsible for implementing metrics that evaluate the end-to-end behavior of the Nuro Driver. These metrics will be used to quantify the safety of the driving behavior in our target ODD. This requires prior experience with the development or verification of behavior planning/prediction systems for robots, and a collaborative nature to work closely with a variety of teams across Nuro: Systems, Onboard Software, Simulation, Product, and Operations. About the Work Develop and implement in Python generalizable metrics to verify the driving behavior of an autonomous vehicle. Leverage a combination of machine learning (ML) models and safety metrics from literature to evaluate the end-to-end driving behavior. Evaluate these metrics on a variety of tests: synthetic and log simulation, on-road logs, closed-course testing data, and third-party acc

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience. Lead the design, implementation, and operation of cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deplo

Zoox is looking for an AWS Cloud Security Engineer to lead the design and implementation of secure, scalable, and software-defined infrastructure in our AWS cloud environment. This role is responsible for establishing best-in-class security practices across AWS, driving automation-first infrastructure security, and partnering with engineering and platform teams to embed security into every layer of our technology stack. You’ll act as a security champion, ensuring that infrastructure designs meet the highest standards of confidentiality, integrity, and availability — while maintaining operational efficiency and scalability through Infrastructure as Code (IaC). In this role, you will: Define and own the multi-year security architecture and roadmap for Zoox's robots and fleet, spanning embedded/firmware, in-vehicle networks, cloud, and supporting infrastructure. Partner with hardware, firmware, autonomy, and infrastructure engineering teams to embed security requirements into system design from the ground up, rather than bolting them on after the fact. Lead threat modeling and architecture reviews for new vehicle platforms and major feature launches, identifying and prioritizing systemic risk across the fleet. Set technical standards and guardrails - secure boot, key management, network segmentation, update/OTA security, and more - and drive their adoption across engineering teams. Represent Product Security in cross-functional and leadership discussions, translating technical risk into business and safety impact for the organization. Qualifications 10+ years of experience in security engineering, including significant time in an architect, staff, or technical lead capacity. Deep expertise in embedded/IoT security, including secure boot, TPM/TEE, cryptographic key management, and hardened firmware/OS design. Demonstrated experience architecting security for complex, physical/cyber-physical sys

Position Overview As a Senior Staff Software Engineer on Diligent's Platform AI team, based out of our technical center of excellence in Vancouver, you will drive the architecture and technical direction of the services that bring AI research and models into production across Diligent's global product suite. You will partner with AI researchers, product managers, and Staff Engineers as peers — leading through influence across the Platform AI organization rather than through reporting authority, on secure, scalable AWS Serverless solutions that translate ML and LLM research into commercial-quality, production systems. Key Responsibilities Drive technical direction and architecture for ML/LLM systems across multiple AI platform teams, partnering with Staff Engineers rather than managing ICs in isolation. Design secure, scalable, fault-tolerant AI/ML solutions using AWS Serverless technology — event-driven, highly observable, with infrastructure as code. Evaluate and prototype new AI technologies (LLM frameworks, model providers, agentic tooling) to guide build-vs-buy decisions across the organization. Serve as the go-to contact for architecture problems and questions across the Platform AI org, and regularly present and guide architecture discussions department-wide. Mentor Staff Software Engineers and Applied Scientists through constructive code review and design partnership. Collaborate with Applied Scientists and Product teams to productize AI capabilities, translating multi-quarter AI strategy into execution roadmaps and representing engineering's perspective to senior leadership. Design, build, and scale search and retrieval systems — including OpenSearch and semantic/vector search — that power discovery, retrieval-augmented generation, and other AI-driven product features. Lead through ambiguity, helping teams navigate undefined problems to successful delivery. Required Experience/Skills 10-15+ years of professional experience developing and owning high-scale, s

Zoox's Robot Software Infrastructure team is seeking a passionate software engineer to help develop and advance the common performant operating system that powers several devices on our vehicle including Autonomy systems. This team develops platform-level software and services, including operating systems that enable complex, hardware-accelerated workloads critical for autonomous driving on automotive-grade hardware. We work closely with cross-functional teams—including developers, release management, hardware engineering, manufacturing and operations—to support vehicle development and deployment at scale. You'll have the opportunity to influence the next generation of our platform, hardware, and robotaxi. If you are excited to explore a broad problem space and are mindful of how components fit within a larger system, you may be a great fit! In this role, you will: Design, develop, and maintain the operating system platform that powers various on-bot devices and applications Architect and implement platform-level software to support robust and scalable robotics infrastructure Configure and manage embedded Linux build systems (e.g., Yocto) and bootloader processes (e.g., U-Boot) to ensure reliable system startup and maintenance Develop and optimize device drivers and kernel-space components using C, C++, or Rust to meet performance and reliability requirements Collaborate cross-functionally to support seamless integration and delivery of the OS platform, triage issues, support new hardware bring-up and manufacturing functions Qualifications 8+ years delivering production systems and software applications, 2+ years of delivering custom Embedded Linux operating systems Have a deep understanding of Linux, build systems like Yocto, and bootloaders like U

As a Technical Lead on Zoox's internal agentic platform, you will own end-to-end integration of a tool-centric agent runtime with external and internal agent clients, line of business backends, scheduled and interactive agent workloads, and cloud operations (Kubernetes, observability, secrets management). You will translate architecture and security intent into stable tool contracts, testable integration milestones, and repeatable releases, and you will be the primary engineer when issues sit at the boundary between product surfaces, platform services, and upstream systems. This role is platform and service integration for an agentic framework that mediates tools (discovery, invocation, policy, and telemetry). Success is measured by reliable tool call paths over HTTP, correct authentication and scoping, environment parity from dev through production, and clear ownership across partner engineering, security, and infrastructure teams. In this role, you will: Own and lead integration strategy and execution across hosted services, shared libraries, standardized tool protocols (e.g., JSON-RPC over HTTP), REST APIs, and diverse callers (vendor agents, consoles, automation workers). Drive cross-functional delivery with backend API teams, partner agent owners, security, SRE/platform, and program management, ensuring formal sign-off where required. Debug and root-cause complex failures using structured logs, distributed traces, metrics, and gateway/session-token behavior, documenting durable mitigations and runbooks. Define and review all integration artifacts (contracts, allowlists, registry config, environment matrices, and interface assumptions) that upstream and downstream teams implement against. Contribute to release gating by ensuring container image promotion, configuration/secrets posture, smoke path execution for high-traffic flows, and disciplined branching/tagging for production inte

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing proble

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. We are seeking a highly motivated Software Development Engineer in Test (SDET) to join the Release Management Team. As a Software Development Engineer in Test on the Release Management team at Zoox, you will help accelerate our software release by ensuring that we are shipping the safest and most reliable software possible. As developers build new features, you will be responsible for developing Hardware-In-Loop tests to support our safety case. These efforts are critical to maintaining our code quality and ensuring our service capabilities are operating as intended. Your ability to understand the overall system design and component interaction to help guide test methodology for functional and safety sign-off is crucial to the overall success of Zoox. Accountability and integrity are core to our team. This role is coding-intensive, focused on building solutions for high-fidelity testing, scalable automation frameworks, and sophisticated data analysis tools to ensure successful compliance to requirements and mission success. In this role, you will: Lead the design, development and maintenance of large-scale event-driven software/hardware -in-the-loop (SIL/HIL) tests and testing frameworks, utilizing advanced software patterns to improve modularity and reduce code duplication. Architect and manage end-to-end continuous integration (CI) pipelines to automate the execution of regression suites. Lead root cause analysis for complex system-level failures, developing log mining scripts and visualization dashboards (e.g., Grafana, SQL-based notebooks) to triage failures and track performance metrics. Perform gap analyses between high-level safety requirements and technical test implementations, including the development of intricate timing and prioritization patterns. Lead end-