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Staff Deep Learning Compiler Engineer
Senior engineer designing and optimizing Quadric's deep learning compiler stack (MLIR, TVM, LLVM) that lowers PyTorch/TensorFlow/ONNX models onto its GPNPU edge-AI processor — graph optimizations, quantization, kernel codegen, benchmarking, and hardware-software co-design with the architecture team.
Staff Machine Learning Engineer, Causal Inference
A Staff Machine Learning Engineer focuses on causal inference at DoorDash, building production systems for uplift models, counterfactual evaluation, and connecting experiments with ML to drive decisions across new verticals like grocery and retail.
Staff Machine Learning Scientist, Applied Causal Inference
Designs, builds, and productionizes causal ML systems (uplift models, heterogeneous treatment effect, counterfactual evaluation) for DoorDash's New Verticals (grocery, retail, etc.) to influence marketplace decisions like promotions and recommendations.
Staff Machine Learning Engineer, Fulfillment Planning
Staff ML engineer on DoorDash's Fulfillment Planning team, building large-scale production ML systems for real-time delivery assignment, routing, and fulfillment/ETA estimation across the logistics network. Day-to-day spans Python, deep learning frameworks, optimization, and ML governance, plus mentoring and setting technical direction.
Staff Machine Learning Engineer, Personalization
Staff ML engineer building production personalization and growth models for DoorDash's consumer search across grocery and retail categories, partnering with product teams and mentoring juniors. Core work centers on Python ML (PyTorch/TensorFlow), causal inference, recommendation systems, and AI coding tools in a hybrid SF/Sunnyvale setup.
Staff Software Engineer, Machine Learning
Builds and ships machine-learning models and optimization algorithms (budget pacing, automated bidding) for DoorDash's ads platform and catalog/product knowledge graph, owning the end-to-end ML lifecycle from training through deployment, experimentation, and monitoring. Hybrid role using PyTorch, PySpark, and Snowflake.
Senior Staff Machine Learning Engineer, Ads
Leads AI-driven ads and promotions delivery systems at DoorDash, designing real-time ranking/relevance models using deep learning, LLMs, and sequence modeling to optimize merchant-consumer matching across search/discovery platforms.
Senior Staff Machine Learning Engineer, Consumer
Leads AI-driven personalization for DoorDash’s consumer shopping journey, designing and deploying ML models to enhance search, discovery, and recommendations across food, grocery, and retail—scaling teams and mentoring engineers to modernize recommendation systems.
Staff Machine Learning Engineer, Compliance Automation (Platform)
Staff ML engineer on Coinbase's Compliance Automation team building production Agentic AI (LLM-powered agents, orchestration pipelines, evaluation frameworks) that automate compliance workflows like investigations and decision support. Core stack: Python, LLM/RAG tooling, LangChain, Airflow, Spark. Remote-first USA role with quarterly in-person surges.
Staff Machine Learning Engineer - Edge AI
Build and optimize AI models for edge devices to improve safety and efficiency in physical operations like transportation and logistics using petabyte-scale sensor and video data.
Staff Machine Learning Engineer, AI Platform & Agentic Apps
Staff-level ML engineer building the agent harness behind every AI agent at Robinhood: orchestration, tool integrations, context/memory, trajectory-level evals, and action guardrails shipped as platform primitives for internal and customer-facing agents. Core stack is Python, LLMs, and distributed systems; hybrid role in Menlo Park, CA.
Staff Machine Learning Engineer, AI Insights
Designs and maintains scalable observability systems (logging, tracing, metrics) for a global AI cloud platform, using tools like Prometheus, Grafana, and Kubernetes.
Staff Machine Learning Engineer
Staff ML engineer on Coinbase's CX Intelligence team, owning end-to-end design and delivery of production machine learning systems (LLMs, deep learning, graph neural networks, classical ML in Python) that power customer support routing, classification, evaluation, and safety. Also mentors engineers and drives technical strategy with cross-functional stakeholders.
Staff Machine Learning Engineer, ML Platform
Staff ML Engineer on Braze's Predictive and Generative AI team, owning the ML platform that trains, deploys, and serves hundreds of customer-specific models at global scale — hands-on work on multi-region serving fleets, orchestration, and CI/deployment tooling. Core stack: Kubernetes, cloud infra, Python, Ruby on Rails, MongoDB, Redis.
Senior Staff Machine Learning Engineer
Senior Staff ML Engineer at Netradyne (fleet safety via computer vision and edge computing) in Bengaluru: owns end-to-end architecture of large-scale cloud ML systems — data ingestion, feature/ETL pipelines, training infrastructure, model serving, monitoring and retraining — using Python, AWS, Gen-AI/LLMs and agentic AI, while setting engineering standards and mentoring senior engineers.
Staff Software Engineer, AI/ML
Staff-level IC on DigitalOcean's Applied Research team, owning the technical direction for feedback-driven learning in agentic AI systems — reward modeling, preference optimization (RLHF, DPO, PPO, GRPO), and evaluation infrastructure — shipping research to production. Hybrid role in Seattle; 8+ years of production AI/ML experience required.
Staff Machine Learning Engineer - Game Tech Group, ML Platform
Architect and scale ML infrastructure for game AI systems, focusing on model serving, orchestration, and deployment workflows to move models from experimentation to production reliably.