Senior Machine Learning Engineer

Motion Recruitment is hiring a Senior Machine Learning Engineer in Wilmington, MA for an onsite role focused on bringing machine learning from raw sensor data to models that run reliably on constrained hardware. This position spans the end to end ML lifecycle, including data pipelines, model development, deployment to edge, and the supporting MLOps infrastructure needed for regulatory and quality workflows.

In this role, you will work with sensor and embedded teams to train and optimize signal processing and anomaly detection models, then integrate and validate inference directly within device software. You will also help shape how sensor data is selected, validated, collected, and organized so model performance can be tracked and improved over time.

Key responsibilities

• Own the full machine learning lifecycle, from raw sensor data to models running on constrained hardware.
• Design and use data pipelines for sensor data.
• Train, optimize, and deploy machine learning models for signal processing and anomaly detection on edge devices.
• Collaborate with embedded engineers to integrate and validate inference within device software.
• Build MLOps infrastructure to support regulatory and quality processes.
• Participate in sensor selection and validation.
• Document model development to support regulatory submissions and internal quality processes.
• Develop and troubleshoot workflows for collecting, cleaning, and organizing sensor data.
• Build and refine ML models for real-time device applications and performance improvements.
• Work with firmware teams to embed and test AI features on hardware platforms.
• Set up and oversee tools for tracking experiments, automating evaluations, and managing deployments.
• Analyze model behavior, ensure reliability, and resolve issues to maintain high-quality outputs.

Required skills and experience

• Python proficiency.
• Hands-on experience with PyTorch or TensorFlow.
• Experience deploying models to edge using TFLite, ONNX, CoreML, TensorRT, or an equivalent approach.
• Experience building sensor data pipelines.
• Proficiency with MLOps.
• Solid software engineering fundamentals.
• Proficiency in C or C++.

Desired skills and experience

• 5 years of machine learning engineering or applied ML.
• Experience with physiological signal processing for medical or wearable applications.
• Background in robotics or autonomous systems.
• Experience in a startup or small team.
• Degree in a relevant field.

Tools and technologies

• Python, PyTorch, TensorFlow
• TFLite, ONNX, CoreML, TensorRT
• MLOps
• C, C++

Compensation and benefits

• Bonus OR Commission eligible
• Medical Insurance
• Dental Benefits
• Vision Benefits
• Paid Time Off (PTO)
• 401(k) {including match - if applicable}