Design and deploy end-to-end AI systems powering real products. Own the full intelligence stack including retrieval, agent orchestration, evals, and governance. Requires Python, LLM experience, and production AI system building.
Build and operate production ML systems and platform components for healthcare technology, partnering with ML and data science teams on model deployment, observability, and reliability.
Staff MLOps Engineer responsible for the reliability, performance, and cost-efficiency of production ML systems. Architect ML platform with feature stores, model registries, and automated CI/CD pipelines.
Senior or Staff Applied Research Software Engineer building AI/ML prototypes and production solutions. Requires 3-5+ years full-stack experience with modern web frameworks, databases, and strong AI-assisted coding skills.
Design and build scalable ML ranking systems powering Reddit's personalized feeds, search, and recommendations at massive scale. Requires 5+ years building large-scale distributed ML systems.
Player-coach role leading a small AI engineering team building natural language analytics and reporting features. Hands-on coding plus management responsibilities for agents, evals, and data systems.
Research intern on the Model Shaping team working on post-training methods, efficient neural network training, and foundation model evaluation. Requires strong ML fundamentals and PyTorch/JAX experience.
Principal Software Engineer leading technical direction for Generative AI and Agentic systems at enterprise scale. Owns AI platform architecture, builds evaluation infrastructure, and drives model strategy across the organization.
Conduct optimization research and implement large-scale constrained optimization models that drive real-time trading decisions, working across the full research lifecycle from theory to production. Requires PhD-level coursework and strong applied research background in optimization.
Senior IC building and maintaining ML underwriting and credit decisioning models for Cash App Borrow and Afterpay. Owns full modeling lifecycle including experimentation, calibration, deployment, and monitoring.
Founding ML Engineer building production ML systems for governance, security, and agentic platform capabilities at Docker. Requires 5+ years applied ML experience shipping systems and 4+ years backend/infra engineering.
Research Engineer optimizing multimodal AI models (video, audio, language) for production using distillation, quantization, sparsification. Focus on latency, cost, quality tradeoffs for real-time generative avatar systems.
Own the policy framework and agent harness for an AI underwriting agent. Design configurable policies, build evals, and ship production LLM/agentic systems. Partner with ML engineers and product leadership on the agentic roadmap.
Staff ML Engineer leading end-to-end identity verification ML systems including document authenticity, face matching, liveness detection, GNN-based identity graphs, and behavioral risk models. Requires 8+ years production ML experience and domain expertise in biometrics or fraud detection.
Technical lead for the shared, accelerator-agnostic inference runtime serving Claude. Owns architecture, performance, and validation for GPU/TPU/Trainium platforms in a high-scale distributed systems environment.
Design, build, and maintain LLM integrations powering AI features. Own end-to-end delivery from requirements through production monitoring with focus on scalability and reliability.
Own ML systems for send-time optimization, propensity modeling, and nudge decisions at consumer scale. Set experimentation standards and mentor a small ML team.
Founding Staff ML Engineer building production ML systems for governance, security, and agentic platform capabilities at Docker. Owns architecture, data pipelines, evaluation, and model lifecycle while mentoring the growing team.
Intern developing and optimizing GPU-accelerated kernels for ML/AI applications. Requires strong GPU programming background (CUDA/Triton) and knowledge of performance optimization.
Research intern on the Inference team building efficient serving systems for large foundation models. Focus on distributed inference, compiler-aware optimization, and novel inference-time strategies.
Principal Engineer setting technical vision and building AI/ML infrastructure for Generative AI and Recommender Systems at Pinterest, scaling to hundreds of millions of inferences per second. Requires deep expertise in distributed systems and proven cross-org technical leadership.
Own evaluation science and post-training methodology for Reddit's foundational LLMs. Define benchmarks, design model-as-a-judge systems, and set SFT recipes that turn base models into safe, Reddit-native endpoints.
Build and deploy production ML solutions for strategic customers, identifying gaps through direct engagement and implementing adaptive systems that evolve with real-world use. Requires 4+ years ML experience and 2+ years customer-facing technical work.
8-month modelling residency embedded in production and research projects, focusing on adaptive algorithms, real-time learning, model efficiency, and cross-stack optimization. Requires Python, deep learning frameworks, and ML optimization experience.
Research Engineer advancing Claude's code generation capabilities through reinforcement learning. Design RL environments, build verifiers, run training experiments on frontier models, and improve training pipelines for real software engineering tasks.
3-month research fellowship for early-career researchers working on frontier Multimodal LLMs, generative modeling, and real-time audiovisual AI. Own a research problem in pretraining, post-training, RL, evaluation, or multimodal modeling. Strong PyTorch and first-author tier-1 paper required.
Staff ML Systems Engineer leading large-scale embedding and recommendation model architecture, distributed training, and real-time serving. Owns ML strategy and mentors engineers on personalization systems.
Build and fine-tune vision-centric VLMs and generative models using Pinterest's visual-text datasets. Requires 2+ years industry computer vision experience and an M.S. or Ph.D.
Build and scale Snowflake's Cortex Training LLM post-training platform, handling distributed GPU scheduling, orchestration, and productionizing research for enterprise-scale model adaptation.
New/recent PhD to own RL and post-training for large-scale omni models. Build and scale the full RL/post-training stack including rollout, optimization, reward modeling, and evaluation for real-time audiovisual AI.
Early-career engineer optimizing inference for real-time multimodal AI avatars. Focus on KV cache strategies, serving frameworks, quantization, and latency reduction for LLMs and diffusion models.
Lead projects building and deploying large-scale ASR/NLP/LLM systems for meeting intelligence. Architect training, fine-tuning, and inference pipelines using PyTorch/JAX and own ML systems from research to production.
Staff ML Engineer setting technical direction for autonomous mineral refining using reinforcement learning and simulation. Owns modeling, validation, and deployment of control systems on live industrial equipment.
Build and deploy reinforcement learning models to autonomously control mineral refining facilities, optimizing recovery rates, energy use, and uptime in real operating plants.
Build and optimize AI agent orchestration and reasoning systems for the insurance industry. Requires 6+ years in ML/AI, strong Python skills, and exceptional LLM prompting ability.
Develop and integrate ML detection and tracking models for autonomous vehicle perception using production pipelines and vehicle sensor data. Requires Python/PyTorch experience and familiarity with modern detection/tracking architectures.
PhD intern role focused on LLM research, large-scale ML systems, and e-commerce applications including search, recommendations, and knowledge graphs. Requires strong ML foundations and programming skills.
PhD intern on Instacart's Economics team building ML solutions at the intersection of economics and machine learning. Requires causal inference expertise, Python/R, and SQL/Pandas fluency.
Build and operate production multi-agent AI systems that turn longitudinal health data into actionable clinical recommendations. Requires 6+ years building production ML or backend systems plus 1+ years building agentic AI.
Principal-level IC building and scaling production autonomous agents and agentic workflows across Block's ecosystem using frontier LLMs. Requires 15+ years experience shipping AI systems from zero to production scale.
Build and productionize AI/ML systems including recommendations, NLP interfaces, and agentic workflows. Requires 10+ years building production-grade AI/ML systems and experience with foundation models.
Build and productionize large-scale recommendation systems, NLP/embedding models, and agentic AI workflows. Requires 6+ years ML/NLP experience and expertise in PyTorch/TensorFlow, RAG, and vector search.
Build evaluation infrastructure and datasets to measure how well AI agents detect misuse and policy violations. Design experiments, productionize evals into release pipelines, and improve safety investigation capabilities.
Staff-level engineer defining and leading AI agent evaluation frameworks, building eval infrastructure, and establishing production observability for LLM-powered systems. Requires 8+ years experience and deep expertise in testing non-deterministic AI agents.
Staff-level engineer building AI data platform infrastructure, eval systems, and agent-first tooling for frontier labs. Requires 4+ years shipping production systems, full-stack experience, and deep TypeScript/Python proficiency.
Staff-level engineer building LLM/ML systems for clinical documentation review, risk detection in healthcare claims, and provider-patient matching at a mental healthcare platform.
Software Engineer building and shipping AI-enabled features and workflows for a healthcare price transparency platform. Requires 2+ years Python experience and SQL knowledge.
Senior Software Engineer building and scaling production AI products including chatbots, document processing, and agentic workflows for an accounting automation platform.
Staff Software Engineer building and scaling Databricks' managed large-scale GPU training platform (AIR). Focus on distributed training performance, scheduling, fault tolerance, and developer experience for thousands of accelerators.
Senior Software Engineer building and scaling Databricks' managed GPU training platform (AI Runtime) for large-scale distributed AI model training. Requires 5+ years in distributed systems and hands-on experience with GPU training frameworks.
Design and deploy end-to-end AI systems powering real products. Own the full intelligence stack including retrieval, agent orchestration, evals, and governance. Requires Python, LLM experience, and production AI system building.
Build and operate production ML systems and platform components for healthcare technology, partnering with ML and data science teams on model deployment, observability, and reliability.
Staff MLOps Engineer responsible for the reliability, performance, and cost-efficiency of production ML systems. Architect ML platform with feature stores, model registries, and automated CI/CD pipelines.
Senior or Staff Applied Research Software Engineer building AI/ML prototypes and production solutions. Requires 3-5+ years full-stack experience with modern web frameworks, databases, and strong AI-assisted coding skills.
Design and build scalable ML ranking systems powering Reddit's personalized feeds, search, and recommendations at massive scale. Requires 5+ years building large-scale distributed ML systems.
Player-coach role leading a small AI engineering team building natural language analytics and reporting features. Hands-on coding plus management responsibilities for agents, evals, and data systems.
Research intern on the Model Shaping team working on post-training methods, efficient neural network training, and foundation model evaluation. Requires strong ML fundamentals and PyTorch/JAX experience.
Principal Software Engineer leading technical direction for Generative AI and Agentic systems at enterprise scale. Owns AI platform architecture, builds evaluation infrastructure, and drives model strategy across the organization.
Conduct optimization research and implement large-scale constrained optimization models that drive real-time trading decisions, working across the full research lifecycle from theory to production. Requires PhD-level coursework and strong applied research background in optimization.
Senior IC building and maintaining ML underwriting and credit decisioning models for Cash App Borrow and Afterpay. Owns full modeling lifecycle including experimentation, calibration, deployment, and monitoring.
Founding ML Engineer building production ML systems for governance, security, and agentic platform capabilities at Docker. Requires 5+ years applied ML experience shipping systems and 4+ years backend/infra engineering.
Research Engineer optimizing multimodal AI models (video, audio, language) for production using distillation, quantization, sparsification. Focus on latency, cost, quality tradeoffs for real-time generative avatar systems.
Own the policy framework and agent harness for an AI underwriting agent. Design configurable policies, build evals, and ship production LLM/agentic systems. Partner with ML engineers and product leadership on the agentic roadmap.
Staff ML Engineer leading end-to-end identity verification ML systems including document authenticity, face matching, liveness detection, GNN-based identity graphs, and behavioral risk models. Requires 8+ years production ML experience and domain expertise in biometrics or fraud detection.
Technical lead for the shared, accelerator-agnostic inference runtime serving Claude. Owns architecture, performance, and validation for GPU/TPU/Trainium platforms in a high-scale distributed systems environment.
Design, build, and maintain LLM integrations powering AI features. Own end-to-end delivery from requirements through production monitoring with focus on scalability and reliability.
Own ML systems for send-time optimization, propensity modeling, and nudge decisions at consumer scale. Set experimentation standards and mentor a small ML team.
Founding Staff ML Engineer building production ML systems for governance, security, and agentic platform capabilities at Docker. Owns architecture, data pipelines, evaluation, and model lifecycle while mentoring the growing team.
Intern developing and optimizing GPU-accelerated kernels for ML/AI applications. Requires strong GPU programming background (CUDA/Triton) and knowledge of performance optimization.
Research intern on the Inference team building efficient serving systems for large foundation models. Focus on distributed inference, compiler-aware optimization, and novel inference-time strategies.
Principal Engineer setting technical vision and building AI/ML infrastructure for Generative AI and Recommender Systems at Pinterest, scaling to hundreds of millions of inferences per second. Requires deep expertise in distributed systems and proven cross-org technical leadership.
Own evaluation science and post-training methodology for Reddit's foundational LLMs. Define benchmarks, design model-as-a-judge systems, and set SFT recipes that turn base models into safe, Reddit-native endpoints.
Build and deploy production ML solutions for strategic customers, identifying gaps through direct engagement and implementing adaptive systems that evolve with real-world use. Requires 4+ years ML experience and 2+ years customer-facing technical work.
8-month modelling residency embedded in production and research projects, focusing on adaptive algorithms, real-time learning, model efficiency, and cross-stack optimization. Requires Python, deep learning frameworks, and ML optimization experience.
Research Engineer advancing Claude's code generation capabilities through reinforcement learning. Design RL environments, build verifiers, run training experiments on frontier models, and improve training pipelines for real software engineering tasks.
3-month research fellowship for early-career researchers working on frontier Multimodal LLMs, generative modeling, and real-time audiovisual AI. Own a research problem in pretraining, post-training, RL, evaluation, or multimodal modeling. Strong PyTorch and first-author tier-1 paper required.
Staff ML Systems Engineer leading large-scale embedding and recommendation model architecture, distributed training, and real-time serving. Owns ML strategy and mentors engineers on personalization systems.
Build and fine-tune vision-centric VLMs and generative models using Pinterest's visual-text datasets. Requires 2+ years industry computer vision experience and an M.S. or Ph.D.
Build and scale Snowflake's Cortex Training LLM post-training platform, handling distributed GPU scheduling, orchestration, and productionizing research for enterprise-scale model adaptation.
New/recent PhD to own RL and post-training for large-scale omni models. Build and scale the full RL/post-training stack including rollout, optimization, reward modeling, and evaluation for real-time audiovisual AI.
Early-career engineer optimizing inference for real-time multimodal AI avatars. Focus on KV cache strategies, serving frameworks, quantization, and latency reduction for LLMs and diffusion models.
Lead projects building and deploying large-scale ASR/NLP/LLM systems for meeting intelligence. Architect training, fine-tuning, and inference pipelines using PyTorch/JAX and own ML systems from research to production.
Staff ML Engineer setting technical direction for autonomous mineral refining using reinforcement learning and simulation. Owns modeling, validation, and deployment of control systems on live industrial equipment.
Build and deploy reinforcement learning models to autonomously control mineral refining facilities, optimizing recovery rates, energy use, and uptime in real operating plants.
Build and optimize AI agent orchestration and reasoning systems for the insurance industry. Requires 6+ years in ML/AI, strong Python skills, and exceptional LLM prompting ability.
Develop and integrate ML detection and tracking models for autonomous vehicle perception using production pipelines and vehicle sensor data. Requires Python/PyTorch experience and familiarity with modern detection/tracking architectures.
PhD intern role focused on LLM research, large-scale ML systems, and e-commerce applications including search, recommendations, and knowledge graphs. Requires strong ML foundations and programming skills.
PhD intern on Instacart's Economics team building ML solutions at the intersection of economics and machine learning. Requires causal inference expertise, Python/R, and SQL/Pandas fluency.
Build and operate production multi-agent AI systems that turn longitudinal health data into actionable clinical recommendations. Requires 6+ years building production ML or backend systems plus 1+ years building agentic AI.
Principal-level IC building and scaling production autonomous agents and agentic workflows across Block's ecosystem using frontier LLMs. Requires 15+ years experience shipping AI systems from zero to production scale.
Build and productionize AI/ML systems including recommendations, NLP interfaces, and agentic workflows. Requires 10+ years building production-grade AI/ML systems and experience with foundation models.
Build and productionize large-scale recommendation systems, NLP/embedding models, and agentic AI workflows. Requires 6+ years ML/NLP experience and expertise in PyTorch/TensorFlow, RAG, and vector search.
Build evaluation infrastructure and datasets to measure how well AI agents detect misuse and policy violations. Design experiments, productionize evals into release pipelines, and improve safety investigation capabilities.
Staff-level engineer defining and leading AI agent evaluation frameworks, building eval infrastructure, and establishing production observability for LLM-powered systems. Requires 8+ years experience and deep expertise in testing non-deterministic AI agents.
Staff-level engineer building AI data platform infrastructure, eval systems, and agent-first tooling for frontier labs. Requires 4+ years shipping production systems, full-stack experience, and deep TypeScript/Python proficiency.
Staff-level engineer building LLM/ML systems for clinical documentation review, risk detection in healthcare claims, and provider-patient matching at a mental healthcare platform.
Software Engineer building and shipping AI-enabled features and workflows for a healthcare price transparency platform. Requires 2+ years Python experience and SQL knowledge.
Senior Software Engineer building and scaling production AI products including chatbots, document processing, and agentic workflows for an accounting automation platform.
Staff Software Engineer building and scaling Databricks' managed large-scale GPU training platform (AIR). Focus on distributed training performance, scheduling, fault tolerance, and developer experience for thousands of accelerators.
Senior Software Engineer building and scaling Databricks' managed GPU training platform (AI Runtime) for large-scale distributed AI model training. Requires 5+ years in distributed systems and hands-on experience with GPU training frameworks.