3 дня назад
Staff ML Ops Engineer (Robotics)
150 000 - 180 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff ML Ops Engineer (Robotics) (Python, Kubernetes, GPU Clusters): Building scalable ML infrastructure, deployment tooling, and data pipelines that support AI and reinforcement learning products for robots with an accent on GPU cluster management, model deployment, and platform observability. Focus on transforming research prototypes into production capabilities, optimizing training and evaluation pipelines, and maintaining reliable ML systems in operation.
Location: Waltham Office, United States
Salary: $150,000–$180,000 annually
Company
develops advanced robotic products and related AI and software technologies.
What you will do
- Implement and maintain tools, infrastructure, and pipelines for the Central Software ML Platform.
- Transform machine learning proofs of concept into scalable solutions for new robot capabilities.
- Own end-to-end delivery across implementation, testing, deployment, and operations.
- Maintain GPU clusters and automate monitoring and cluster-health improvements.
- Monitor platform health, investigate root causes, and optimize ML data, training, and evaluation pipelines.
- Collaborate with ML engineers, researchers, and cross-functional stakeholders while mentoring peers.
Requirements
- Eligible to work in the United States; visa sponsorship is not available.
- 5+ years of experience as a Senior Software Engineer or ML Engineer.
- Proficiency in Python and ML frameworks including PyTorch, TensorFlow, Pandas, and NumPy.
- Experience with cloud platforms and scalable deployment tools such as GCP or AWS, Docker, Kubernetes, Ansible, and Terraform.
- Experience managing and scheduling GPU clusters, applying CI/CD to ML pipelines, and using experiment or model-versioning tools.
- Experience building scalable data and ETL pipelines, plus collaborative Agile or Scrum development.
Nice to have
- Networking fundamentals including IAP, Tailscale, Shared VPC, and NAT.
- Database optimization knowledge, including indexing and connection pooling.
- TypeScript, Node, and full-stack web technologies for internal MLOps tooling and dashboards.
- Experience with on-robot or edge deployment constraints and annotation tools such as SAM or Co-Tracker.
Culture & Benefits
- Collaborative work with ML/RL engineers and researchers across the organization.
- Participation in an Agile development process with regular coordination and progress communication.
- Medical, dental, and vision benefits.
- 401(k), paid time off, and an annual bonus structure.
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