Gravis Robotics

Machine Learning Engineer

• Own the MLOps technical vision and roadmap, aligning infrastructure investments and architecture decisions with company and engineering milestones
• Lead and build an engineering team architecting, building, and optimizing high-throughput data ingestion pipelines and platform infrastructure for petabyte-scale multimodal datasets
• Mentor and grow team members through continuous feedback, career development, and technical guidance
• Design, build, and operate high-availability hybrid cloud and on-premise compute clusters
• Provide developers and researchers with a seamless, unified compute experience
• Lead continuous deployment and monitoring pipelines for ML models deployed across thousands of edge devices in the field
• Establish full model lifecycle management, including model registries, artifact versioning, automated regression testing, and real-time observability and monitoring
• Collaborate with robotics engineers to translate requirements into reliable, scalable training environments
• Evaluate and integrate MLOps tooling on cloud and on-premise compute platforms

Data & ML Ops Lead