Machine Operator Integrator Jobs

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: Design, implement, and operate cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deploy them efficiently in our robotaxi. Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware

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: Design, implement, and operate cutting-edge ML training performance optimization techniques — distributed training (data/tensor/pipeline parallelism), mixed-precision, gradient checkpointing, and GPU kernels — to scale our VLM, VLA, and Foundational models training efficiency. <

As the Manager of Model Validation & Verification (VnV) for Behavior Autonomy, you will lead an engineering and data science team responsible for evaluating, benchmarking, and validating the machine learning models and behavioral algorithms that drive our autonomous vehicle (AV) prediction and planning stacks. You will own the statistical frameworks, offline/online evaluation metrics, and validation pipelines that ensure our behavioral models operate safely, comfortably, and predictably. Operating at the intersection of Data Science, Machine Learning, and Safety Engineering, you will partner closely with Autonomy Software, Prediction, Planner, and ML Operations teams to establish data driven release criteria for our AV fleet. In this role, you will: Team Leadership & Execution: Lead, mentor, and scale a high-performing team of Data Scientists, ML Validation Engineers, and Software Engineers while driving roadmaps, sprint execution, resource allocation, and high-throughput model releases with rigorous safety guardrails. Culture of Rigor: Foster a culture of statistical excellence, healthy skepticism, proactive risk tracking, and data-driven decision-making. Validation Strategy & Methodologies: Define and execute end-to-end validation strategies across offline evaluation, open/closed-loop simulation, and shadow-mode fleet benchmarking to ensure robust behavioral model performance. Statistical uncertainties, and regressions into clear, data-driven recommendations for release gating and executive leadership. Metrics, Release Gating & Rigor: Oversee metric development and standardization with System Safety and Autonomy teams, establishing quantitative go/no-go release criteria for Behavioral Planner and Prediction ML models while fostering statistical rigor and proactive risk management. Cross-Functional & Infrastructure Partnership: Partner closely with Planner, Prediction, MLOps

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 ML and CV to make autonomous driving as seamless as possible. The Opportunity Would you like to be part of the ML Training platform team that enables autonomous driving, driving scenario understanding, learned planning and trajectories, large scale driving simulations and several other ML use cases at Zoox? You will get to work across all ML teams within Zoox - Foundation Models, Perception, Prediction, Planner, Simulation, Data Science, Collision Avoidance, etc. and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. The ML Training platform team builds and operates the core part of the ML platform that powers model training at scale. We are responsible for developing and operating ML tools, deep learning frameworks, and distributed model training infrastructure to support foundational models and reinforcement learning. This team also owns the model repository and model lifecycle management tools used by our applied research teams for in- and off-vehicle ML use cases. You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. In this role, you will: Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient. Design, implement, and operate a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models. Co

Perplexity is seeking top-tier AI Research Scientists and Engineers to advance our AI products and capabilities. We're building the future of AI-powered search and agent experiences through our Sonar models, Deep Research Agent, Comet Agent, and Search products. Join us in creating SOTA experiences that handle hundreds of millions of queries and continue to scale rapidly. Team Structure Depending on your interests and expertise, you'll work on one of three specialized teams: 1. Core Research Team (Horizontal) Focus on generating and improving base models that power all our products. This team works on foundational model capabilities, post-training techniques, building RL infra and infrastructure that benefits the entire organization. 2. Agent Products Team (Vertical) Concentrate on fine-tuning and optimizing models for our Deep Research Agent and Labs/Canvas products. This team bridges research and product, ensuring our agent capabilities deliver exceptional user experiences. 3. Comet Agent Team (Vertical) Dedicated to developing and enhancing our Comet Agent product. This specialized team focuses on the unique requirements and optimizations needed for Comet's specific use cases. Responsibilities Research & Development Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO) Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products Stay current with the latest LLM research, especially in model training, optimization, and personalization techniques Implement preference optimization and personalization capabilities to enhance user experience Invent in-house improvements and optimizations to enhance SOTA models Turn research ideas into algorithms and run experiments to launch new models Infrastructure & Implementation Own full-stack data, training, and evaluation pipelines required for model development Build robust and effective training frameworks (on

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. We are seeking a highly motivated software development engineer in test (SDET). This role is central to leading the creation of automation frameworks, tools, and processes for platform safety clearance and system testing. The ideal candidate is passionate about developing high-quality, robust, optimized, and reusable software infrastructure, and is eager to advance their skills in complex systems thinking and validation problem-solving. Some examples of tools this role has supported in the past: * Front and back end of Streamlit web-app to automate tracking requirements to test case traceability. * Automation framework for execution of safety critical tests. * CI/CD job to identify affected requirements and HIL tests from code changes and automate the execution of all linked tests. In this role, you will: Create tools and web-apps to help us automate and streamline manual clearance processes. Propose tools and/or feature ideas to the team to improve processes. Develop software for automated validation frameworks for system level testing in Hardware In the Loop (HIL), simulation environments, and post-processing of test data. Develop and maintain dashboards to illustrate progress against targets and highlight focus areas. Execute, triage, and debug automated verification and validation system tests. Qualifications B.S. or higher in Mechanical Engineering, Electrical Engineering, Systems Engineering, Computer Engineering, Computer Science or a related technical degree. Experience developing automated test frameworks and tools for

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 looking for a Director, Marketing Analytics to translate our marketing intelligence strategy into operational excellence and commercial impact. You will lead a multidisciplinary analytics team across data engineering, analytics engineering, visualization, and data science workflows. Sitting at the intersection of marketing strategy, revenue operations, and data engineering, you will serve as a trusted partner to Sales, RevOps, Finance, Product-Led Growth (PLG), and Enterprise Data. You will build our marketing intelligence system. This will focus on three key areas. First, you will optimize how we allocate capital. You will use solid ROI and incrementality frameworks for this. Second, you will identify growth insights by finding predictive buyer and expansion signals. Finally, you will promote data clarity. This involves ensuring we have a well-governed, transparent single source of truth. Grounded in open, explainable attribution models, you will streamline organization-wide decision-making and help fuel long-term growth across the entire customer lifecycle. What You Will Be Doing Capital Allocation & Attribution: Operationalize open, explainable multi-touch attribution (MTA) and ROI frameworks that measure full-funnel contribution and ensure global budgets are allocated efficiently . Customer Journeys & Predictiv

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 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 an Applied AI team member at Anthropic, you will be a pre-sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with both the Claude API and Claude for Work Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide tech

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 an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with both the Claude API and Claude for Work Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guid

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 Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Staff level Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Responsibilities Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable) Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability Build robust systems for data quality assurance and validation at scale Collaborate with research teams to implement novel data processing architectures Build and operate end-to-end data pipelines that turn raw web-scale corpora into training-ready datasets You may be a good fit if you have: 5+ YOE outside of internships Strong software engineering skills with experience building high-throughput fault-tolerant distributed systems Hands-on experience with distributed computing frameworks, particularly Apache Spark Excellent problem-solving skills and attention to detail Strong communication skills and ability to work in a collaborative environment Advanced degree in Computer Science or related field Experience with language model training infrastructure Background in Data Infrastructure, MLOps, or ML infrastructure Stro

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 team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. This role combines deep computational biology expertise with frontier AI capabilities, positioning Anthropic at the forefront of AI-driven scientific discovery. As one of the first computational members of this Life Sciences research group, you'll work on a high-impact team that operates at the intersection of computational and experimental biology. You'll bring broad computational biology experience to bear across the team's projects, driving discoveries from large-scale computational analysis of biological data through to results our experimental scientists can test, and moving flexibly between problems as the science demands. You'll have substantial access to Claude and you'll help establish how computational biology operates at Anthropic. This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for scientific understanding and biomedicine. If you're excited about using your computational expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you. Key responsibilities Build, run, and maintain the analysis pipelines that back the team's experimental programs: sequence a

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 Anthropic's Safeguards organization builds the policies, evaluations, and enforcement systems that keep our models from contributing to catastrophic harm. We are hiring a manager to lead the research engineering team responsible for biological safety: the evaluations, datasets, and classifiers that govern how our models handle biological knowledge. You will lead a team of research scientists and engineers who design and run capability evaluations against frontier models, curate training data for our safety classifiers, train and iterate on those classifiers alongside our ML engineers, and measure how they hold up against adversarial pressure in production traffic. You will set the technical direction for that work, decide where the team invests, and own the results. This is a hands-on management role. Most of your time goes to growing and directing the team, but you will keep enough technical depth to review an eval design, interrogate a classifier's failure modes, and represent the work credibly to Research, Product, and Policy partners. The core tension your team owns is precision: safeguards need to be robust against sophisticated actors while staying out of the way of the far larger population of legitimate researchers using Claude to accelerate life sciences work. Getting that tradeoff right is an empirical problem, and your team is the one measuring it. Key responsibilities Manage, coach, and grow a team of research scientists and engineers working on biological safety evaluations and classifiers, including hiring, onboarding, performance, and career development Set the technical direction and roadmap for the biol