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Senior Machine Learning Engineer, Data Mining

3 hours, 23 minutes ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
AWS Azure CI/CD GCP LLM Machine Learning MLOps Python PyTorch Reinforcement Learning System Design TensorFlow
Apply Now
Motional

Motional

Motional is a leading company in driverless technology and autonomous vehicles, leveraging decades of industry expertise to develop and deploy safe and reliable autonomous vehicles. With a powerful DNA combining Aptiv's automotive technology and Hyunda...

Automotive
1K-5K
Founded 2020
$20M raised
View All Jobs

Description

  • Design and implement teacher-student model frameworks for multimodal sensor data.
  • Develop training pipelines for knowledge distillation and compressed model evaluation.
  • Build and scale reinforcement learning policy-learning and reasoning systems for autonomous driving applications.
  • Implement and optimize RL training workflows such as PPO, DQN, and actor-critic methods.
  • Deploy distilled and RL models into production with backend engineers.
  • Optimize inference for latency, throughput, and hardware efficiency across GPU and CPU clusters.
  • Implement model versioning, A/B testing, and performance monitoring.
  • Prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior.
  • Establish production patterns for graceful degradation, fault tolerance, cost optimization, and operational reliability.
  • Collaborate with ML scientists, data engineers, and autonomy teams, and mentor junior engineers.

Requirements

  • BS in Computer Science, Machine Learning, or a 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, including loss functions, training strategies, and evaluation of compressed models.
  • Proven experience with reinforcement learning in production or research settings, including policy optimization, reward design, simulation environments, and RL-based reasoning.
  • Expert-level proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong software engineering fundamentals, including testing, CI/CD, containerization, and system design.
  • Experience deploying ML models in cloud environments such as AWS, GCP, or Azure and optimizing them for inference.
  • Demonstrated ability to ship production-grade ML systems and mentor team members.
  • MS or PhD in Computer Science, Machine Learning, or a related field is preferred.
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning is preferred.
  • Background in autonomous driving, robotics, or real-time decision-making systems is preferred.
  • Familiarity with multimodal learning, sensor fusion, or embodied AI is preferred.
  • Experience building active learning loops, ML-based data mining, or contrastive learning is preferred.
  • Knowledge of model serving tools such as TF Serving, Triton, or TorchServe and MLOps platforms is preferred.
  • Publications or open-source contributions in RL, distillation, or efficient ML are preferred.

Benefits

  • Base salary range of $172,000 to $229,000 USD.
  • Additional compensation may include a bonus and company equity.
  • Medical, dental, and vision insurance.
  • 401(k) with company match.
  • Health savings accounts.
  • Life insurance.
  • Pet insurance.
  • Hybrid schedule with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote work option.

Interested in this position?

Apply directly on the company website

Apply Now

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