Senior Machine Learning Engineer ml/python/Wilmington ma

Overview You will own the end-to-end ML lifecycle for sensor data, delivering models that run on constrained hardware. Collaborating with embedded and firmware teams, you will design data pipelines, train and deploy models for signal processing and anomaly detection, and build MLOps infrastructure. You will support regulatory submissions and internal quality with well-documented model development. This role offers impact on edge AI in medical/robotic domains within a hands-on, cross-functional team. Compensation / BenefitsMedical InsuranceDental BenefitsVision BenefitsPaid Time Off (PTO)401(k) including match Responsibilitiesown the full ML lifecycle from raw sensor data to edge-running modeldesign and implement sensor data pipelinestrain, optimize, and deploy ML models for signal processing and anomaly detection on edge devicescollaborate with embedded/firmware teams to integrate and validate inferencebuild MLOps infrastructure and toolingparticipate in sensor selection and validationdocument model development for regulatory submissions and quality processesdevelop and troubleshoot workflows for collecting, cleaning, and organizing sensor databuild/refine ML models for real-time device applications and performance improvementsset up tools for tracking experiments, automating evaluations, and managing deploymentsanalyze model behavior, ensure reliability, and resolve issues Key requirementsStrong proficiency in PythonHands on experience in PyTorch or TensorFlowExperience deploying models to edge using TFLite, ONNX, CoreML, TensorRT, or equivalentExperience building sensor data pipelinesProficiency with MLOpsSolid Software engineering fundamentalsProficiency in C or C++PythonPyTorchTensorFlowTFLiteONNXCoreML