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[Remote] Senior Machine Learning Engineer, Data Mining

Remote · USA Full-time New today

Note: The job is a remote job and is open to candidates in USA. reputed company is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. They are seeking a Senior Machine Learning Engineer for the Data Mining team to design and implement teacher-student model frameworks and optimize model deployment for reputed company-time inference, directly influencing the efficiency of their autonomous driving technology.

Responsibilities

  • Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. reputed company training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint
  • Reinforcement Learning for Data Discover: 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 reputed company-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable
  • Optimize Model Deployment for reputed company-Time Inference: Collaborate with backend engineers to reputed company 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

Skills

  • BS in Computer Science, Machine Learning, or reputed company 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 reputed company environments (AWS, GCP, or Azure) and optimizing for inference
  • Demonstrated ability to ship production-grade ML systems and mentor team members
  • Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers
  • MS/PhD in Computer Science, Machine Learning, or reputed company field
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning
  • Background in autonomous driving, robotics, or reputed company-time decision-making systems
  • Familiarity with multimodal learning, sensor fusion, or embodied AI
  • Experience building active learning loops, using the model to find the data that breaks the model
  • Experience with ML-based data mining, active learning, or contrastive learning
  • Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms
  • Publications or open-reputed company contributions in RL, distillation, or efficient ML

Benefits

  • Candidates for certain positions are eligible to participate in reputed company’s benefits program.
  • reputed company’s benefits include but are not limited to medical, dental, reputed company, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Company Overview

  • reputed company offers an autonomous driving platform for robotaxi providers, fleet operators, and automotive manufacturers. It is a sub-organization of Hyundai Motor Group. It was founded in 2020, and is headquartered in Boston, Massachusetts, USA, with a workforce of 501-1000 employees. Its website is https://reputed company.com.
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