Build the tasks, rewards, environments, and data systems used to train and evaluate coding agents. The role requires strong software engineering fundamentals and experience with infrastructure, data, or distributed systems; reinforcement learning experience is a plus.

Trains and fine-tunes large-scale diffusion transformer models for image and video generation, conducts rigorous ablation studies, and optimizes distributed training. Requires hands-on diffusion-model experience, strong PyTorch and transformer expertise, and understanding of generative-model evaluation.

Build and operate AI-powered, customer-facing workflows for Datadog Notebooks, combining reliable backend systems with LLM capabilities. The role requires 6+ years of engineering experience, Go or Python expertise, and experience delivering production AI products.

Leads the platform, evaluation, governance, economics, and internal enablement required to operate AI systems reliably in production. Requires hands-on ML/AI, data platform, or AI operations experience, strong LLM fluency, and the judgment to guide investment and build-versus-buy decisions.

Own the shared AI foundation powering Aleph’s financial planning products, including model routing, context and tool systems, evaluations, and observability. The role requires Staff-level experience shipping production LLM and agentic systems, strong technical judgment, and a pragmatic builder’s mindset.

Build and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.

Build and operate agentic AI systems for rare disease research, including typed workflows, evaluation, observability, and production deployment. The role requires a bachelor’s degree or equivalent experience, 5+ years building production systems, and 2+ years shipping LLM-powered applications.

Build AI agent harnesses, models, and product capabilities that enable agents to perform complex work across digital environments. The role combines applied AI research and software engineering, requiring Python proficiency, strong product judgment, and experience with agent tooling, reinforcement learning, or browser technologies.

Build and deploy secure enterprise AI agents, integrations, and automated workflows that improve internal productivity and business operations. The role requires at least five years of enterprise, software, automation, or IT systems engineering experience, plus hands-on workflow and LLM application development.

Build and deploy production machine-learning models and data systems that classify and enrich Internet telemetry for internal platforms and customer-facing products. The role requires 5+ years of applied ML, data science, or software engineering experience, plus strong Python or Go skills.

Leads development and integration of advanced maritime autonomy for USVs, UUVs, and cooperating UAVs, including motion planning, localization, safety, and multi-agent coordination. Requires staff-level technical leadership, substantial robotics experience, C++ and Python proficiency, and eligibility for a SECRET clearance.

Build and integrate AI/LLM capabilities for a customer and partner portal, including RAG, agents, retrieval systems, and evaluation pipelines. The role requires 3+ years of AI/ML engineering experience, strong Python skills, and production experience serving and evaluating LLMs.

Senior machine learning engineer who will build and operate large-scale AI systems for Airbnb’s payments ecosystem, including LLM agents, fraud defenses, and personalization. The role requires 5+ years of applied AI/ML experience, strong Python or Java skills, and production MLOps expertise.

Research Scientist II building and improving fraud risk models and scam detection systems using audio, behavioral, and metadata signals. Requires an advanced degree and 3+ years of applied ML experience with Python and modern ML frameworks.

Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.

Senior Staff ML Engineer fine-tunes and optimizes state-of-the-art LLMs for Airbnb's customer support AI products, including AI assistants and autonomous agents. Partners cross-functionally to productionize models at scale. Requires PhD and 10+ years experience with PyTorch.

Leads architecture and technical direction for agentic search systems combining LLMs, retrieval, and content-understanding pipelines for contract intelligence. The role requires 10+ years building production systems, deep search or LLM expertise, and strong cross-team technical leadership.

Leads technical strategy for Reddit’s Ads ML Platform, improving feature development, training-data generation, experimentation, and the path to production ML serving. The role requires 8+ years in infrastructure or distributed systems, production ML platform experience, and strong cross-team technical leadership.

Own the architecture and delivery of production AI systems for patient-provider matching, search relevance, personalization, clinical workflows, and engagement. The role requires extensive software engineering, distributed systems, search or recommendation, ML applications, and foundation-model experience in a regulated healthcare setting.

Build and productionize AI-powered features, evaluations, and data and inference pipelines. The role requires Python web development experience, hands-on LLM or generative AI work, retrieval architectures, and an understanding of model quality, cost, and latency tradeoffs.

Build production AI agents and the distributed platform that operates large-scale GPU infrastructure. The role requires 5+ years of backend, distributed systems, or infrastructure experience, with expertise in agent systems, knowledge graphs, retrieval, or semantic search.

Build and operate large-scale machine learning systems for financial data quality, transaction categorization, risk scoring, and enrichment. The role requires 10+ years shipping production ML systems, strong framework and pipeline expertise, and the ability to mentor engineers and collaborate across teams.

Build and deploy LLM-powered tools, agents, and ecosystem infrastructure with life sciences research institutions. The role requires deep scientific or biomedical research experience, production software development expertise, and the ability to translate partner workflows into scalable AI systems.

Build datasets, evaluations, and scalable data systems that improve frontier AI models on challenging biological and scientific tasks. The role partners with scientists and AI labs and requires at least two years of experience applying biology and AI, plus hands-on LLM experience.

Own end-to-end development, evaluation, and production deployment of AI models serving high-volume real-time products. The role requires 5+ years of production Python experience, hands-on fine-tuning and ML operations, cloud infrastructure expertise, and strong technical ownership.

Build and optimize the production LLM inference runtime for frontier models on OpenAI’s custom silicon. The role spans scheduling, distributed execution, memory and KV-cache management, performance tooling, and hardware-software co-design.

Build and deploy AI-powered features for conversation intelligence, developing production ML pipelines and inference services for voice and messaging data. The role requires 2+ years of applied ML experience, Python, an ML framework, NLP familiarity, and cloud infrastructure experience.

Build and deploy explainable machine learning, NLP, LLM, and agentic systems that power enterprise go-to-market intelligence products. The role requires 6+ years of production ML experience, strong Python and cloud skills, and end-to-end ownership from modeling through monitoring.

Build and ship locally hosted language-model capabilities for a cybersecurity product, owning training data, fine-tuning, evaluation, security, and constrained-hardware inference. The role requires strong Python, LLM serving and grounding experience, with Rust and cybersecurity knowledge valued.

Senior software engineer developing ML-based search relevance and discovery systems, including query understanding, ranking, retrieval, and evaluation pipelines. The role requires 5+ years of search relevance experience and expertise in NLP, LLMs, or related discovery technologies.

Owns the full lifecycle of data and ML solutions, from ingestion and feature-ready datasets through production deployment and business-impact measurement. The role combines data engineering, applied machine learning, MLOps, and generative AI to build risk detection capabilities.

Build marketplace search and ranking features while supporting MLOps infrastructure, model deployment, feature stores, and real-time data pipelines. The role requires 5+ years of software engineering or MLOps experience, backend or full-stack expertise, and familiarity with cloud and machine learning tooling.

Research, prototype, and ship statistical and machine learning features that improve MongoDB’s fleet stability, release safety, resource efficiency, and operational automation. The role requires 5+ years of hands-on ML development, strong Python and systems-design skills, and a master’s degree or equivalent quantitative experience.

Researcher focused on scaling reinforcement learning for frontier models, with ownership spanning asynchronous RL algorithms, inference and distributed training systems, and large-scale empirical studies. Requires strong Python and deep learning experience, scalable systems debugging, and rigorous research judgment.

Develop and productionize machine- and deep-learning algorithms for biosignal and EEG data used in medical devices, clinical development, and diagnostics. The role requires 4+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated environments and production ML practices.

Build autonomy and sensor-integration software for autonomous mining vehicles, spanning perception, localization, mapping, planning, control, and field validation. Requires a bachelor’s degree, 2+ years in autonomy or embedded software, C++/Python, robotics middleware, and hands-on multi-sensor fusion experience.

Build and scale post-training, reinforcement-learning, evaluation, and inference systems for long-horizon agents operating over complex enterprise software. The role requires strong Python and PyTorch or JAX skills, distributed GPU experience, empirical rigor, and the ability to take research results into production.

Build and operate production AI agents that transform enterprise processes, data, and code. The role focuses on tool layers, retrieval, context management, evaluations, monitoring, auditability, and guardrails, requiring strong Python and TypeScript plus experience with production LLM systems and traditional machine learning.

Build and deploy embedding, sequence, and language-model representations for Reddit Ads, taking ML projects from requirements and experimentation through production. The role requires 5+ years of end-to-end industry ML experience, with expertise in NLP or computer vision and deep-learning frameworks.

Build production agent systems that plan, use tools, recover from failures, and improve over time. The role requires 5+ years of production ML or backend experience, LLM or agent deployment experience, and expertise in evaluation, tracing, observability, and agent architecture.

Own inference-stack cost and performance by optimizing serving, caching, batching, quantization, decoding, routing, and GPU execution. The role requires 5+ years in ML systems, inference infrastructure, or performance engineering, plus strong Python and systems-language skills.

Build and deploy production AI systems, including agentic workflows, RAG applications, and LLM-powered services. The role requires 5+ years of engineering experience, strong Python skills, cloud and containerization experience, and the ability to lead technical initiatives and mentor engineers.

Develop multimodal perception and authentication systems combining visual, audio, and other sensor signals for real-world AI products. The role requires machine learning expertise, practical research-to-system experience, and proficiency in Python and PyTorch with comfort in C++.

Leads an applied machine learning organization responsible for fraud detection and identity verification models, combining people management with hands-on technical direction. Requires extensive ML leadership, production modeling experience, strong Python skills, and expertise operating in sensitive risk-focused domains.

Leads and manages an applied machine learning team developing production fraud detection and identity verification models. The role combines people leadership with hands-on technical work and requires substantial ML experience, production deployment expertise, and experience in risk-focused domains.

Build and operate production machine-learning systems for search ranking, relevance, extraction quality, and LLM-driven features. The role requires production ML ownership, ranking or relevance expertise, large-scale data experience, Python, and rigorous experimentation skills.

Build evaluation methods, RL environments, agent tooling, and scalable infrastructure that make subjective qualities such as design and taste measurable for frontier AI models. The role requires experience with evaluations, RL environments, ML or post-training, plus strong backend engineering skills.

Develop and deploy machine learning systems for Instacart’s advertising ecosystem, spanning data pipelines, model architectures, serving, experimentation, and optimization. The role requires a graduate degree and strong programming, analytical, and collaboration skills, with experience in large-scale ML systems preferred.

Own the end-to-end lifecycle of memory features for AI agents. Fine-tune models, implement research, build evaluations, and ship production systems with Engineering.

Develop and deploy production machine learning models for real-time inventory and shelf-stocking intelligence at scale. The role requires 5+ years of production ML experience, strong Python and ML framework skills, cloud and data pipeline expertise, and a bachelor's degree or equivalent experience.