We're making driverless vehicles a safe, reliable, and accessible reality.
Senior Machine Learning Engineer, Data Mining
Location
United States
Posted
2 days ago
Salary
$172K - $229K / year
Seniority
Senior
No structured requirement data.
Job Description
Senior Machine Learning Engineer, Data Mining
Motional
Role Description As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of our ML-powered multimodal data mining framework, Omnitag. You will: - Architect and Train Distilled Models: - Design and implement teacher-student model frameworks for multimodal sensor data. - Develop training pipelines for knowledge distillation. - Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint. - Reinforcement Learning for Data Discovery: - Build RL-based policy learning and reasoning systems for autonomous driving applications. - Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. - Explore reward shaping, environment modeling, and multi-agent RL where applicable. - Optimize Model Deployment for Real-Time Inference: - Collaborate with backend engineers to deploy distilled and RL models into production. - Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. - Implement model versioning, A/B testing, and monitoring for performance regressions. - Research and Integrate Agentic Systems: - Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. - Integrate such systems into our broader autonomy stack as experimental or production components. - Drive Production Reliability: - Establish patterns for graceful degradation, fault tolerance, and cost optimization. - Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence. - Mentor and Collaborate: - Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. - Guide junior engineers in best practices for model training, evaluation, and deployment. Qualifications - BS in Computer Science, Machine Learning, or related field, or equivalent professional experience. - 6+ years of hands-on experience in machine learning engineering, with a focus on model post-training, optimization, and deployment. - Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models. - Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning. - Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX). - Strong software engineering fundamentals: testing, CI/CD, containerization, and system design. - Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference. - Demonstrated ability to ship production-grade ML systems and mentor team members. Requirements - Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers. Benefits - Medical, dental, vision. - 401k with a company match. - Health saving accounts. - Life insurance. - Pet insurance. - And more. Salary Range $172,000 — $229,000 USD
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