What we needWe are seeking a Senior ML Operations Engineer with strong machine learning fundamentals and hands-on software engineering experience. This individual will help productionize ML systems, improve robot health monitoring capabilities, build scalable deployment pipelines, and collaborate with ML researchers to bring new models into production robot environments. The ideal candidate combines machine learning expertise with MLOps, distributed systems, and robotics experience.
What you'll do- Build and improve machine learning deployment infrastructure for large-scale robotic fleets.
- Partner with ML researchers to transition new models from experimentation into production.
- Design and implement predictive health monitoring solutions for autonomous robotic assets.
- Create automated monitoring, telemetry analysis, dashboards, and KPI reporting systems.
- Develop data pipelines for dataset curation, labeling, training, validation, and model evaluation.
- Deploy and optimize ML models using ONNX, TensorRT, Docker, and edge computing platforms.
- Improve model rollout, validation, and fleet-wide deployment processes.
- Develop simulation and validation environments to accelerate model testing and software releases.
- Work with software, hardware, computer vision, and operations teams to improve robot reliability and system performance.
- Support computer vision applications including case detection, classification, dimension estimation, and robotic decision-making systems.
- Contribute hands-on Python development and machine learning model architecture design.
What You'll Need- Minimum of 4 years of related experience.
- Strong hands-on Python development skills.
- Experience building machine learning models from scratch.
- Experience with PyTorch and/or TensorFlow.
- Experience with predictive modeling and time-series analysis.
- Strong understanding of machine learning deployment and operationalization.
- Experience with Kubernetes, Docker, Git, Jenkins, and CI/CD environments.
- Experience with SQL and large-scale data systems.
- Experience working with telemetry, sensors, or operational data.
- Experience building monitoring solutions, observability platforms, or analytics dashboards.
- Demonstrated cloud experience with Azure and/or GCP.
- Strong collaboration skills in cross-functional engineering environments.
- Bachelor's degree in computer science, Robotics, Software Engineering, Machine Learning, or related fields.
Preferred Qualifications- Robotics experience.
- Signal processing experience.
- Edge AI and embedded systems experience.
- Computer vision experience.
- Experience deploying models to GPU-accelerated environments.
- Experience with simulation environments or digital twins.
- Experience supporting ML systems running in production at scale.
Our environment- Up to 10% of travel may be required. Employees must have a valid driver's license and the ability to drive and/or fly to client and other customer locations.
- The employee is responsible for owning a credit card and managing expenses personally to be reimbursed on a bi-weekly basis.
#LI-Hybrid
The base range for this position in the posted location is $120,000.00 - $165,000.00 however, base pay offered may vary depending on job-related knowledge, skills, and experience. The compensation package includes medical, dental, vision, disability, 401K, PTO and/or other benefits.
