Cloud ML Platform Engineer

The Role

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 were deploying it. With a team that helped put self-driving cars on public roads at Waymo scaled systems for Segments $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 100000 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

Our roles are often flexible. If you dont fit all the criteria or are in another location (especially one where we have an office like SF of NY) please apply anyway! Wed love to consider you.

Join the team bringing advanced autonomy to the built world

At Bedrock weve assembled one of the most experienced autonomous technology teams in the industry with deep expertise scaling breakthroughs across transportation infrastructure and enterprise software. Our leaders helped put the first self-driving cars on public roads at Waymo scaled systems for Segments $3.2B acquisition and grew Uber Freight to $5B in revenue.

While others debate the future of AI were deploying it in the real world. Our systems are already installed on heavy machines across the country learning on real construction sites and working to reshape the earth with survey-grade precision and exceptional safety. This isnt a simulationits autonomous intelligence working on billion-dollar infrastructure projects.

In just over a year weve raised $80M put our equipment into the field and established partnerships with forward-thinking contractors who are integrating our technology into their operations. Were working quickly to close the gap between Americas surging demand for housing data centers manufacturing hubs and the construction industrys growing labor shortage.

Here algorithms meet steel-toed boots. Youll collaborate with both construction veterans and experienced engineers tackling problems where your work directly impacts how the physical world get built. If youre interested in applying cutting-edge technology to solve meaningful problems alongside a talented teamwed love to have you join us.