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As a Senior Machine Learning Platform Engineer, you will manage ML infrastructure, optimize pipelines, mentor junior engineers, and ensure observability and compliance in production environments.

The Forward Deployed Engineer will lead deployments of autonomous systems, ensuring performance and reliability while collaborating with customers and engineering teams.

Design and develop scalable full-stack applications using various technologies, collaborate with teams, and optimize performance in robotics AI systems.

The Robotics Autonomy Engineer will develop and implement autonomy software, integrate systems, conduct field testing, and collaborate across teams for performance enhancement in robotic solutions.

The Robotics Autonomy Engineer will design and deploy motion planning and control algorithms for robots, focusing on navigation and trajectory generation in unpredictable environments.

Build and maintain CI/CD pipelines and cloud-native, containerized infrastructure (Kubernetes/Docker) for robotics and AI systems. Deploy and support workloads across cloud and edge, improve developer workflows through automation, and collaborate with robotics, ML, and platform teams to ensure reliability, observability, and scalable deployments for distributed robotic systems.

Design, build, and maintain production data pipelines and infrastructure for robot telemetry, logs, sensor data, and events. Implement ingestion, transformation, and orchestration (Airflow), backend services/APIs, and AWS-based storage/processing. Improve reliability with monitoring, retries, schema validation, and data quality checks. Collaborate with robotics, ML, and deployment teams to scale data systems for fleet operations.

Design, develop, and deploy production-grade 3D mapping systems and pipelines. Lead end-to-end field deployment, validation, and customer handoff. Build tooling, benchmark reliability, troubleshoot software/hardware/networking issues, and translate field feedback into engineering improvements to support mission-critical autonomous robot deployments.

Lead planning and delivery of 3D mapping projects, contribute to mapping software development, deploy mapping systems and pipelines, validate algorithms on robots, manage cross-functional teams, track progress with PM tools, mitigate risks, and build documentation and playbooks to scale execution.