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NVIDIA

Designs the chips and software that power AI

Senior Robotics Manipulation Manager - Software Engineering, Robotics Manipulation

Full-Time
$272k - $488.8k/yr+ Equity
Senior, Expert
Bachelor's, Master's, PhD
Austin, TX, USA+5 moreMore locations: Santa Clara, CA, USA | Durham, NC, USA | Reston, VA, USA | Boulder, CO, USA | Charlottesville, VA, USA
In Person
Engineering ManagementEngineering Leadership
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience)
  • 12+ total years of relevant industry experience building robotics or robotics-adjacent systems, including 3+ years leading, mentoring, and managing engineering teams.
  • Robotic arm depth. Hands-on expertise with robotic arms, manipulation, and physics from grasping, motion planning (across both numerical optimization and sampling-based approaches), and control (including force/impedance and contact-rich control) to perception-guided manipulation.
  • Accelerated compute. Working understanding of GPU-accelerated computing and modern ML infrastructure, and how to architect robotics software to take advantage of it (CUDA, PyTorch, GPU-accelerated simulation, edge inference).
  • Partner and developer interface. Demonstrated ability to work directly with external partners, customers, and developer communities and to translate their needs into roadmap and shipping product.
  • Technical credibility. Strong software engineering fundamentals (modern C++ and Python) and the ability to engage substantively in technical and architectural decisions with your team.
Responsibilities
  • Lead the Isaac Manipulation team. Recruit, grow, and mentor a high-performing team of robotics software engineers; set direction, raise the technical bar, and manage the team’s health, velocity, and delivery.
  • Shape the roadmap. Collaborate with Product Management to define and drive the strategy and roadmap for grasping, motion planning and control, perception-for-manipulation, and learned manipulation policies — from research to productized, supported platform capabilities.
  • Apply creative solutions to real industrial problems. Translate the hardest contact-rich manipulation tasks in manufacturing, logistics, assembly, and machine tending into robust capabilities that work in the real world, not just the lab.
  • Bridge research and product. Partner with NVIDIA Research, the Isaac Sim/Lab teams, and foundation-model teams (e.g., Isaac GR00T, Cosmos) to bring sim-to-real, imitation, and reinforcement learning approaches into the platform and onto physical arms.
  • Engage partners and developers. Serve as a technical face of Isaac Manipulation to robot-arm OEMs, system integrators, and the developer community — gathering requirements, running joint engineering, and ensuring our APIs and tools meet real workflows. Support our ecosystem of developers through responsible migration handling of their solutions built on our durable platform.
  • Leverage accelerated compute. Drive architecture and execution that fully uses NVIDIA GPUs, CUDA, and the accelerated-computing stack across simulation, training, and on-robot inference on Jetson and edge platforms.
  • Deliver. Drive planning and execution of complex, multi-functional programs; own quality, performance, and the real-world deployment of learned policies and manipulation stacks on physical robots.
  • Influence the strategy. Represent manipulation in platform-level technical and business decisions, and help shape where NVIDIA invests across the robotics stack.
Desired Qualifications
  • Industry leadership and fluency. Experience building manipulation or industrial automation products at an established robot-arm company or manipulation startup, and a strong understanding of the product landscape including use cases, the integrators, and the platforms from leading vendors.
  • Hardware-agnostic platforms. A track record building developer-facing or low-code platforms and tooling that abstract across multiple robot-arm brands and make manipulation accessible to non-experts.
  • Learned manipulation. Deep experience with imitation learning, reinforcement learning, sim-to-real transfer, or manipulation foundation models, and shipping learned policies onto real hardware.
  • Ecosystem & OSS. Contributions to ROS 2, ros2_control, MoveIt, or the broader robotics open-source and standards community.
  • Founder / 0-to-1 instincts. Experience starting or scaling a product or team from the ground up and operating with speed in ambiguous, fast-pace problem spaces.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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