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CoreWeave

Rents GPU cloud computing for AI developers

Manager, Field Engineering (Physical AI)

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Engineering, Physics, Mathematics, or a related technical discipline, or equivalent practical experience.
  • At least 10 years of experience in technical consulting, field engineering, product engineering, applied artificial intelligence, or a related customer-facing engineering discipline.
  • At least 5 years of experience leading and developing technical teams in a fast-moving environment, including hiring strong people, setting a clear bar, and creating an environment where specialists can do their best work.
  • Sufficient technical depth in artificial intelligence and machine learning applied to physical systems or engineering workflows to engage credibly with machine learning engineers, data scientists, controls engineers, simulation specialists, and engineering leaders, and to make sound judgments about data, modeling, validation, and deployment trade-offs.
  • Experience partnering across Product, Engineering, Sales, Marketing, and Field Engineering to align priorities and move work from customer signal to delivered capability.
  • Ability to clearly articulate complex technical topics to technical, executive, and customer audiences in writing and verbally.
  • Ability to access export-controlled information under the stated U.S. export-control eligibility criteria.

Responsibilities

  • Evolve the regional operating model for Physical AI Field Engineering from opportunity qualification and problem framing through data exploration, model development, deployment, adoption, and expansion.
  • Lead, coach, and develop a high-performing team of Specialist Field Engineers, Forward Deployed Data Scientists, and Forward Deployed Engineers, including hiring, workforce planning, career development, performance management, and succession planning.
  • Set the technical and delivery bar for customer engagements, ensuring teams build solutions grounded in engineering criteria, validated against physical constraints, and deployed into workflows where they create measurable value.
  • Partner directly with strategic customers and senior stakeholders across automotive, robotics, aerospace, and industrial engineering to understand priorities, shape technical strategy, and maintain executive confidence throughout delivery.
  • Work with Account Executives, Account Managers, Account Solutions Architects, Technical Solutions Managers, Product, Engineering, and Platform teams to qualify opportunities, allocate specialist capacity, and create a consistent customer experience.
  • Build mechanisms to improve team effectiveness at scale, including reusable engagement patterns, delivery standards, onboarding, enablement, technical reviews, and knowledge-sharing practices.
  • Establish a field-to-product feedback loop by identifying recurring customer needs, distinguishing reusable product opportunities from one-off delivery work, and translating field evidence into actionable recommendations for Product and Engineering.
  • Own operating metrics for customer value, time to deployment, software adoption, delivery quality, team capacity, expansion, and infrastructure or software-as-a-service opportunities created through engagements.
  • Represent Physical AI Field Engineering internally and externally, explaining how domain expertise, applied artificial intelligence, and the platform combine to solve engineering problems.

Desired Qualifications

  • Experience in automotive, robotics, aerospace and defense, industrial, manufacturing, or another engineering-intensive industry.
  • Experience delivering or supporting artificial intelligence solutions in embedded, on-site, production, or safety-critical environments.
  • Familiarity with modern machine learning platforms and workflows spanning experimentation, model management, data exploration, application development, and cloud deployment.
  • Ability to own capacity models, hiring plans, technical career frameworks, delivery key performance indicators, or portfolio-level planning across multiple customer engagements.
  • Track record of converting repeated customer problems into reusable software, product capabilities, or standardized delivery patterns.

About the Company

CoreWeave

Rents GPU cloud computing for AI developers

CoreWeave rents cloud computing to AI labs and businesses that train models and run them in production for research and commercial applications. Its platform combines NVIDIA graphics chips, storage, networking, and software built for demanding AI workloads across connected clusters scaled to fit each project. CoreWeave Forge connects tools for tracking experiments, testing models, and improving AI systems using feedback from production. Customers rent computing capacity through committed contracts or usage charges, while managed services handle the infrastructure needed to keep large workloads running. CoreWeave was founded in 2017 and is headquartered in Livingston, New Jersey.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Livingston, NJ
Founded
2017

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