Senior Machine Learning Engineer, Data Mining

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Senior Machine Learning Engineer focused on designing multimodal models for autonomous vehicle data mining. Collaborating on data discovery workflows and optimizing model efficiency in production environments.

Posted 7/30/2026full-timeBoston • Massachusetts, Nevada, Pennsylvania • 🇺🇸 United StatesSenior💰 $172,000 - $229,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and implementing machine learning models, particularly in model distillation and reinforcement learning, with a strong focus on optimizing deployment for real-time inference. Proven ability to mentor and collaborate with cross-functional teams to deliver production-grade systems.

Highest-signal resume keywords

Model DistillationReinforcement LearningPython ProgrammingML Frameworks (PyTorch, TensorFlow, JAX)Cloud Deployment (AWS, GCP, Azure)

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Applicant Tracking System Keywords

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Hard Skills

Model Post TrainingModel OptimizationModel DeploymentPolicy OptimizationReward DesignSimulation EnvironmentsTestingCI/CDContainerizationSystem Design

Soft Skills

MentoringCollaboration

Tools & Technologies

GPU/CPU ClustersA/B TestingMonitoring ToolsOmnitag

Industry Keywords

Machine Learning EngineeringAutonomous DrivingAgentic SystemsOperational ExcellenceFault Tolerance

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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 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 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.

Requirements

What you’ll need

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.
Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Benefits

Comp & perks

medical
dental
vision
401k with a company match
health saving accounts
life insurance
pet insurance