Leads engineering for Spotify’s Conversation Product Area, including shared agent infrastructure, evaluation systems, search, and voice platforms. The role manages approximately 70 engineers and requires deep technical leadership across large-scale ML platforms, agent systems, search, or speech infrastructure.

Build and productionize AI-native products and platform components, including LLM and agentic systems, while driving scalable architecture, operational excellence, and rapid iteration. The role requires extensive software engineering experience and a track record of shipping complex production systems.

Build and productionize AI and machine learning systems that transform Airbnb’s customer support experience, collaborating with product, design, and engineering teams. The role requires 2–4 years of ML engineering experience, advanced education or equivalent experience, and fluency in English and Mandarin.

Build production AI applications, agentic workflows, backend services, and enterprise integrations for Finance. The role requires 5+ years of production software engineering experience, strong Python and backend fundamentals, and experience with scalable, secure distributed systems.

Leads the end-to-end development, deployment, and optimization of machine learning models for cybersecurity and malware detection. The role requires 5+ years of production machine learning experience, strong Python and ML framework expertise, and technical leadership across data, evaluation, and MLOps workflows.

Leads development of scalable machine learning infrastructure, models, and internal platforms for voice and speech GenAI products. Requires extensive ML/AI experience, expertise in modern LLM techniques and audio models, distributed systems, cloud deployment, and production-scale data platforms.

Build and lead Sweep’s production AI decision system, converting noisy cyber-physical signals into reliable operational decisions across edge and cloud environments. The role requires 5–10 years of end-to-end production systems experience, strong Python and systems design skills, and comfort working in high-stakes deployments.

Builds benchmarks, model evaluations, and backend infrastructure for an AI data platform’s Benchmarks and Evaluations vertical. The role requires 4+ years of engineering experience, hands-on model evaluation, and prior ownership of backend and infrastructure systems.

Leads the technical AI strategy and production application of LLMs, NLP, retrieval, agents, and multimodal systems for large-scale legal discovery. Requires 8+ years of software engineering experience, including significant ML/AI leadership and production LLM experience.

Build and scale AI-powered features for internet-scale security intelligence, including LLM and RAG systems, analytics, and workflow automation. The role requires 5+ years of software engineering experience, strong Python skills, and experience delivering secure, user-facing AI applications.

Build production LLM-powered systems for Instacart’s AI-for-Data platform, including retrieval, agentic workflows, evaluations, and internal data tools. The role requires strong Python backend engineering, SQL and data infrastructure experience, applied LLM expertise, and at least five years of professional experience.

Leads development and deployment of autonomy software for satellites and missile-defense systems, spanning optimization, tasking, planning, and sensor or track fusion. The role requires 7+ years of related experience, strong C++ and Python skills, robotics expertise, and the ability to obtain a SECRET clearance.

Leads technical direction and develops autonomy algorithms and high-performance software for satellite and missile-defense applications. The role requires deep robotics, optimization, control, and unmanned-systems expertise, along with significant experience integrating capabilities into real-world platforms.

Build and deploy autonomy software for satellites and missile-defense systems, spanning optimization, tasking, scheduling, track fusion, and motion planning. The role requires strong C++ and Python skills, robotics or unmanned-systems experience, simulation expertise, and the ability to obtain a SECRET clearance.

The Senior AI Developer will productionize and operate multimodal models and reasoning agents for millions of users, building model-serving, evaluation, observability, and reliability infrastructure. The role requires production cloud-services experience, ML systems expertise, and a bachelor's degree.

Leads development of systems that optimize AI agents for cost, latency, and quality, with emphasis on agentic coding and reliable production software. Requires 8+ years of experience, strong concurrency and API design skills, and fluency in multiple programming languages.

Build and productionize large-scale generative speech models for voice conversion and related capabilities. The role combines research, data, evaluation, distributed training, performance optimization, and responsible deployment of speech systems.

Build and ship AI-powered features for incident detection, triage, resolution, and observability workflows. The role requires strong production software engineering experience, practical LLM and GenAI expertise, cloud-native exposure, and a pragmatic approach to rapid experimentation.

Leads a team of machine learning researchers and engineers developing web-scale recommendation systems, guiding strategy, research-to-production execution, and cross-functional delivery. Requires 7+ years of post-graduate academic and industry experience, 3+ years of people management, advanced education, and strong ML publication credentials.

Develops and optimizes reinforcement learning systems and infrastructure for training large AI models like Claude, focusing on performance, reliability, and researcher productivity. Requires 4+ years software engineering experience.

Build scalable, fault-tolerant platforms for serving large language models across research and production environments. The role requires 4+ years of backend systems experience, strong programming skills, and familiarity with LLM serving, containers, cloud infrastructure, and infrastructure as code.

Conduct applied AI research by designing, evaluating, and optimizing machine-learning models and code, with a focus on PyTorch, GPU performance, and generative AI systems. Requires a PhD or postdoctoral degree and 1–3+ years of ML engineering or data science experience.

Builds advanced AI agents and machine-learning solutions for enterprise customers, translating business needs into production systems. Requires strong engineering skills, Python proficiency, cloud experience, and a data-driven approach to model development.

Build and deploy end-to-end AI applications and model evaluation systems for global public sector clients. The role requires 7+ years of engineering experience, production AI/ML experience, and proficiency in modern programming languages and cloud platforms.

Build and evaluate reliable agentic AI systems for high-stakes public-sector applications, spanning applied research, model optimization, safety, and benchmarking. The role requires strong Python and AI infrastructure experience, production engineering rigor, and expertise in LLM evaluation or red-teaming.

Leads the architecture and operation of a multi-tenant AI/ML platform supporting production models, LLMs, and agents in regulated scientific environments. Requires 10+ years in distributed cloud-native systems, strong TypeScript and Python skills, production LLM/RAG experience, and technical leadership.

Conduct large-scale reinforcement learning experiments, develop long-horizon benchmarks, investigate scaling behavior, and translate validated research into production training recipes. The role requires strong empirical research skills, Python, distributed ML experience, and a bachelor's degree or equivalent experience.

Research Engineer on a pretraining team, developing and scaling large language models through research, experimentation, infrastructure optimization, and model engineering. Requires advanced ML or computer science education, strong software engineering skills, and expertise in Python and deep learning frameworks.

Build and operate high-performance distributed inference infrastructure serving Claude across large-scale accelerator fleets. The role requires strong software engineering experience with production distributed systems, Kubernetes, cloud platforms, and machine learning infrastructure.

Build and improve production ML and LLM-powered systems that enhance AI Assistant and autonomous-agent quality through evaluation, retrieval, personalization, and orchestration. Requires 2+ years of industry experience, strong coding ability, and experience shipping applied ML systems.

Build advanced search quality systems using machine learning, including personalization signals, ranking models, and domain-adapted LLMs for enterprise search. Requires 2+ years experience in ML, search/NLP, strong coding in Python/Go/Java/C++, and bachelor's in CS/math.

Design and deploy scalable safeguards that mitigate cybersecurity misuse by frontier AI models across OpenAI product surfaces. The role requires deep learning and transformer expertise, software engineering fundamentals, LLM fine-tuning experience, and cross-functional collaboration.

Develops reinforcement learning, memory, and personalization capabilities for frontier models, including long-horizon evaluations and research code. The role requires strong RL research experience, rapid iteration, and the ability to translate rigorous research into product impact.

Build and operate production machine-learning infrastructure, automate model lifecycle workflows, and productionize models across distributed systems. The role requires advanced Python, distributed computing, data engineering, SQL, and hands-on MLOps experience, with Kubernetes and cloud infrastructure experience preferred.

Build and deploy cutting-edge Agentic AI and LLM systems to transform Airbnb's customer service experience, including Chat and Voice AI assistants. Requires 6+ years experience with production ML/AI systems at scale.

Builds production inference infrastructure for in-house AI models, including model serving, GPU optimization, deployment safety, benchmarking, and runtime reliability. Requires 6+ years of software engineering experience and strong backend, Kubernetes, Linux, and distributed-systems skills.

Build and own production AI systems, including agentic workflows, RAG applications, evaluation pipelines, and LLM-powered services. The role requires 5+ years of relevant engineering experience, strong Python skills, and expertise deploying reliable AI applications.

Build and optimize the backend TTS layer for next-generation AI agents, integrating speech vendors, improving latency and naturalness, and implementing persona systems. The role requires production Python, speech ML, linguistic optimization, cloud API, evaluation, and prompt-engineering experience.

This senior applied ML role builds and deploys optimization-driven machine learning systems for serverless infrastructure, spanning cluster management through query compilation. It requires production ML experience, cloud and distributed-systems knowledge, strong programming skills, and a master's degree in a related computational field.

Staff engineer driving technical vision and architecture for Spark Structured Streaming. Build core capabilities like advanced state management and operators; improve latency, throughput, and cost. Requires 8+ years in big-data, Spark, or database systems plus passion for distributed systems.

Senior engineer building and deploying production AI agents and frontier systems for enterprise customers. Combines latest LLMs, reasoning, retrieval, multi-agent architectures with structured knowledge and traditional ML to solve real business problems across industries. Requires 5+ years experience, strong Python, LLM production experience, and customer-facing skills.

Build and scale AI platforms for Rippling's Data Cloud, focusing on schema retrieval, query planning, LLM training pipelines, RL environments, and agent harnesses for intelligent workforce workflows. Requires 8+ years experience with production LLMs, distributed systems, and cloud infrastructure.

Build and deploy production AI agents and frontier systems for enterprise customers, combining LLMs with retrieval, memory, multi-agent architectures, and traditional ML. Design evaluations, run experiments, ensure reliability/safety, and translate customer problems into scalable AI solutions. Requires 4+ years applied AI/ML experience and strong Python skills.

Design and optimize distributed infrastructure and training pipelines for large-scale language and multimodal models. The role requires 3+ years of distributed systems or ML infrastructure experience, PyTorch, cloud platforms, container orchestration, and distributed training expertise.

Build and own the production execution and evaluation platform for Supabase's internal AI agents and operating system. Enforce governance through code with risk tiers, durable state, human gates, and comprehensive observability on GCP with Python.

Build and scale trustworthy AI agent infrastructure at Nuro, focusing on closed-loop evaluation, agent runtime/platform with isolation, and autoresearch systems for autonomous AI-driven engineering workflows. Requires deep LLM expertise, production agent experience, and strong backend/distributed systems skills.

Build and ship production LLM-powered features for aviation safety and efficiency, including RAG, tool-calling, evals, guardrails, and monitoring for cost/latency/quality. Requires prior shipped LLM applications, strong production coding, and RAG depth; hybrid in San Carlos with multiple seniority levels available.

Build and own AI-assisted engineering tools, conventions, context layers, and evaluation frameworks inside a large Rails monolith to scale AI usage across engineering, product, and design teams. Requires 7+ years production software experience with recent Rails and LLM-backed system expertise.

Leads architecture and hands-on development of secure, production-grade AI applications, including LLM orchestration, RAG pipelines, agentic experiences, and resilient backend services. Requires 12+ years of software engineering experience, strong Python and frontend expertise, and technical leadership across global teams.

Serve as technical SME driving adoption of agentic AI platform across departments. Build AI observability dashboards, govern vendor risks, integrate AI systems, and create repeatable IT workflows for safe, scalable generative AI use.