Cloud - ML Platform Engineer

We are looking for Senior or Staff level ML Platform Engineers to join our team in either New York or San Francisco. 

Bedrock Robotics is transforming the physical world with autonomy. While others debate the future of AI, we're deploying it. With a team that helped put self-driving cars on public roads at Waymo, scaled systems for Segment's $3.2B acquisition, and grew Uber Freight to $5B in revenue, and with the backing of world-class advisors and investors from 8VC, Eclipse, Valor, Two Sigma, and many others, we are uniquely positioned to succeed in our optimistic vision of autonomy and industrial transformation.

At Bedrock Robotics, ML Platform Engineering bridges infrastructure and machine learning. We build modern systems for high scale training of end-to-end autonomy, focus on system performance for GPUs, and build solutions for data mining, metrics, labeling, experiment tracking, and evaluation. We are the engine that powers Bedrock Robotics’ fast-moving and novel physical world autonomy.

As a passionate ML Platform engineer, you will have an immediate impact on our autonomy progress. We are looking for experienced Senior Software Engineers / TLs experienced with ML platforms and who can work closely with ML engineers and other infrastructure teams.

Also, you get to drive 100,000 lb excavators.

Some of the challenges our team takes on include:

• Build out robot data labeling and evaluation pipelines.

• Design and create a data mining solution.

• Iterate and evolve experiment tracking.

• Improve performance of our scaled training loop.

• Work with other ML teams to understand their workflows and their needs.

• Develop, maintain, and enhance frameworks for AI/ML model development and deployment while establishing and driving best practices in MLOps 

• Design, advocate, and implement for usability, reliability, scalability, operational excellence, and cost management while delivering incrementally.

• Collaborate closely with ML Engineers, Data Scientists, Data Engineers and Product Managers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process.

Required Qualifications: 

• 5+ years of professional software engineering experience building ML platforms, infrastructure, or internal tooling that accelerates model development and deployment for ML engineers.

• 4+ years of experience (may include graduate research) as an ML, Data, Platform, or Distributed Systems Engineer working on large-scale, complex, or highly distributed systems.

• 2+ years of hands-on experience designing, building, and operating production-grade ML systems, such as training pipelines, feature stores, model serving, evaluation frameworks, or workflow orchestration.

• Proven experience leading projects end-to-end, from concept and initial design through implementation and deployment, working with at least one other engineer.

• 2+ years of close collaboration with cross-functional ML stakeholders to understand requirements and ship platform capabilities that improve iteration speed and reliability.

Preferred Skills/Qualifications: 

• Experience in performance optimization for GPUs

• Experience working with multi-modal data is a plus

• Startup experience is a plus 

• Experience with robotics, simulation, or perception ML pipelines

• Familiarity with modern ML infra stacks (Ray, Kubeflow, MLflow, Metaflow, Airflow, Feast, Vertex, SageMaker, etc.)

• Hands on experience in distributed training, model optimization, or experiment tracking systems

• Experience building internal developer platforms or self-service tooling