Senior ML Operations Engineer
$120k - $165kFull-time
Symbotic LLC
Who We Are With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system – reinventing warehouse automation for increased efficiency, speed and flexibility. What We Need We 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.
- 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.
- 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.
- 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.
Vacancy posted 4 days ago
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