- Robot type
- Warehouse and Logistics
- Location
- WilmingtonNorth CarolinaUSA
- Job type
- Artificial Intelligence
- Posted
- Sep 13, 2026
- Salary
- $120,000–$165,000 a year
Senior ML Operations Engineer
Job description
We do not discriminate based on race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.
Symbotic is an automation technology leader reimagining the supply chain with its end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset for the world’s largest retail, wholesale, and food & beverage companies.
We are a community of innovators, collaborators and pioneers who embrace our differences, because we know unique perspectives make us stronger and smarter. Every perspective matters.
Job responsibilities
- 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.
Job requirements
- 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.
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