6 дней назад
Senior ML Operations Engineer (Robotics)
120 000 - 165 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior ML Operations Engineer (Robotics) (Python/PyTorch/Kubernetes): Building and operating machine learning deployment infrastructure, monitoring systems, and data pipelines for large-scale autonomous robotic fleets with an accent on production ML, predictive robot health monitoring, and edge deployment. Focus on deploying and validating models with ONNX and TensorRT, developing fleet-wide rollout and simulation environments, and improving reliability across robotic systems.
Location: Wilmington, Massachusetts, USA; hybrid work. Up to 10% travel to client and customer locations may be required.
Salary: $120,000–$165,000 base annually, plus benefits.
Company
develops AI-powered robotic and software platforms for warehouse automation and supply chain operations.
What you will do
- Build and improve ML deployment infrastructure for large-scale robotic fleets.
- Transition ML models from research into production robot environments.
- Develop predictive health monitoring, telemetry analysis, dashboards, and KPI reporting for robotic assets.
- Create data pipelines for dataset curation, labeling, training, validation, and model evaluation.
- Deploy and optimize models with ONNX, TensorRT, Docker, and edge computing platforms.
- Develop simulation and validation environments and collaborate with software, hardware, computer vision, and operations teams to improve robot reliability.
Requirements
- At least 4 years of related experience and a bachelor's degree in computer science, robotics, software engineering, machine learning, or a related field.
- Strong hands-on Python development and experience building ML models from scratch.
- Experience with PyTorch and/or TensorFlow, predictive modeling, and time-series analysis.
- Experience with Kubernetes, Docker, Git, Jenkins, CI/CD, SQL, and large-scale data systems.
- Experience with telemetry, sensor or operational data, monitoring solutions, observability platforms, or analytics dashboards.
- Cloud experience with Azure and/or GCP and the ability to collaborate across engineering functions.
Nice to have
- Experience in robotics, signal processing, edge AI, embedded systems, or computer vision.
- Experience deploying models to GPU-accelerated environments.
- Experience with simulation environments, digital twins, or production ML systems at scale.
Culture & Benefits
- Medical, dental, vision, and disability coverage.
- 401(k), paid time off, and additional benefits.
- Collaborative environment spanning software, hardware, computer vision, and operations.
- Valid driver's license required for travel to client and customer locations.
- Business expenses are reimbursed bi-weekly after personal payment.
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