What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical ... Deep experience with imitation learning, reinforcement learning, sim-to-real transfer, or ...
What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical ... Deep experience with imitation learning, reinforcement learning, sim-to-real transfer, or ...
Artificial Intelligence/Machine Learning Engineer (AI/ML)
Chantilly, VA · On-site
$100K - $200K/yr
... and reinforcement learning * Build, train, and tune predictive models using state-of-the-art ... Bachelor's plus two years, Master's plus zero years, or PhD plus zero years * Experience:
Artificial Intelligence/Machine Learning Engineer (AI/ML)
Chantilly, VA · On-site
$100K - $200K/yr
... and reinforcement learning * Build, train, and tune predictive models using state-of-the-art ... Bachelor's plus two years, Master's plus zero years, or PhD plus zero years * Experience:
VIE - Digital Engineer F/H
Lynchburg, VA · On-site
... and reinforcement learning methods. • Familiarity with optimization algorithms, constraint ... Preferred : • PhD in Computer Science, Data Science, Nuclear Engineering, Applied Mathematics, or ...
VIE - Digital Engineer F/H
Lynchburg, VA · On-site
... and reinforcement learning methods. • Familiarity with optimization algorithms, constraint ... Preferred : • PhD in Computer Science, Data Science, Nuclear Engineering, Applied Mathematics, or ...
Autonomy Engineer (Chantilly, VA; Denver Metro Area; Herndon, VA; Hybrid; Northern Virginia)
Chantilly, VA · Hybrid
$140K - $190K/yr
Experience implementing, applying, and analyzing behavior of reinforcement learning algorithms ... This is a full time position
Autonomy Engineer (Chantilly, VA; Denver Metro Area; Herndon, VA; Hybrid; Northern Virginia)
Chantilly, VA · Hybrid
$140K - $190K/yr
Experience implementing, applying, and analyzing behavior of reinforcement learning algorithms ... This is a full time position
Autonomy Engineer (Chantilly, VA; Denver Metro Area; ...)
Chantilly, VA · On-site
$140K - $190K/yr
Experience implementing, applying, and analyzing behavior of reinforcement learning algorithms ... This is a full time position
Autonomy Engineer (Chantilly, VA; Denver Metro Area; ...)
Chantilly, VA · On-site
$140K - $190K/yr
Experience implementing, applying, and analyzing behavior of reinforcement learning algorithms ... This is a full time position
Senior Data Scientist
$140K - $190K/yr
S government * MS degree with 3+ years of experience, and/or PhD in Statistics, Data Science ... models, reinforcement learning, deep learning architectures, and large language models
Senior Data Scientist
$140K - $190K/yr
S government * MS degree with 3+ years of experience, and/or PhD in Statistics, Data Science ... models, reinforcement learning, deep learning architectures, and large language models
Lead Algorithm & Signal Processing Engineer
$157K - $220K/yr
... reinforcement learning, approaches such as Bayesian, deep convolutional and graph neural network ... Pay Information Full-Time Salary Range: $157,000 - $220,000 The salary range listed is based on ...
Lead Algorithm & Signal Processing Engineer
$157K - $220K/yr
... reinforcement learning, approaches such as Bayesian, deep convolutional and graph neural network ... Pay Information Full-Time Salary Range: $157,000 - $220,000 The salary range listed is based on ...
To accomplish this, we leverage supervised and reinforcement learning to predict customer needs and ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
To accomplish this, we leverage supervised and reinforcement learning to predict customer needs and ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
To accomplish this, we leverage supervised and reinforcement learning to predict customer needs and ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
To accomplish this, we leverage supervised and reinforcement learning to predict customer needs and ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
Autonomy Algorithms Lead Software Engineer
Arlington, VA · On-site +1
$173K - $216K/yr
MS or PhD in Computer Science or related technical field * Experience with the following ... Reinforcement learning * Agentic AI * Programming for embedded and physical devices * Multi-agent ...
Autonomy Algorithms Lead Software Engineer
Arlington, VA · On-site +1
$173K - $216K/yr
MS or PhD in Computer Science or related technical field * Experience with the following ... Reinforcement learning * Agentic AI * Programming for embedded and physical devices * Multi-agent ...
Autonomy Algorithms Senior Software Engineer
Arlington, VA · On-site +1
$134K - $184K/yr
MS or PhD in Computer Science or related technical field * Experience with the following ... Reinforcement learning * Agentic AI * Experience programming for embedded and physical devices
Autonomy Algorithms Senior Software Engineer
Arlington, VA · On-site +1
$134K - $184K/yr
MS or PhD in Computer Science or related technical field * Experience with the following ... Reinforcement learning * Agentic AI * Experience programming for embedded and physical devices
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
... large-scale, Reinforcement Learning-based recommender systems that will power personalized ... The minimum and maximum full-time annual salaries for this role are listed below, by location.
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...
... into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
... into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a ... A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics ...
Fulltime Reinforcement Learning Phd information
What is the difference between Fulltime Reinforcement Learning Phd vs Machine Learning Engineer?
| Aspect | Fulltime Reinforcement Learning Phd | Machine Learning Engineer |
|---|---|---|
| Required Credentials | PhD in Computer Science, AI, or related field | Bachelor's or Master's in CS, AI, or related field |
| Work Environment | Research-focused, academic or R&D labs | Industry, product development teams |
| Employer & Industry Usage | Universities, research institutions, tech companies | Tech companies, startups, enterprise firms |
| Common Search & Comparison | Yes | No |
Fulltime Reinforcement Learning Phds typically focus on research and theoretical development in AI, often working in academic or R&D settings. Machine Learning Engineers apply AI techniques to develop practical applications in industry. While both roles require strong AI knowledge, the Phd emphasizes research, whereas the Engineer emphasizes implementation.
What are popular job titles related to Fulltime Reinforcement Learning Phd jobs in Virginia?
For Fulltime Reinforcement Learning Phd jobs in Virginia, the most frequently searched job titles are:
- Internship Zbrush Character Artist
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- Hourly Google Gemini
- Remote Aws Certified Machine Learning Specialist
- Independent Contractor Paraprofessional
- Network Administrator Intern
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- Internship Junior Agronomist
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What job categories do people searching Fulltime Reinforcement Learning Phd jobs in Virginia look for?
The top searched job categories for Fulltime Reinforcement Learning Phd jobs in Virginia are:
What cities in Virginia are hiring for Fulltime Reinforcement Learning Phd jobs?
Cities in Virginia with the most Fulltime Reinforcement Learning Phd job openings:
Full-time
Re-posted 14 days ago
Nvidia rating
9.6
Based on 17 frontline employees who took The Breakroom Quiz
7th of 246 rated software companies
Job description
NVIDIA is the engine of modern AI, and robotics is where AI meets the physical world. The Isaac robotics platform - spanning Isaac Sim, Isaac Lab, Isaac ROS, the foundation models behind Isaac GR00T, and the accelerated libraries that run on Jetson and in the data center - is how the world's developers and industrial leaders build intelligent robots.
We are looking for an exceptional engineering leader and manager to head up Isaac for Manipulation: giving robotic arms and dexterous systems the perception, grasping, motion, and learned skills they need to do real, impactful work. You will be responsible for the strategy, roadmap, and execution for Manipulation - turning hard, contact-rich problems in manufacturing, logistics, and industrial automation into shipping capabilities that our partners and developers can build on. This is a high-visibility role with direct line of sight to the most consequential problems in robotics today. You will grow and mentor a team of world-class robotics and machine-learning engineers, set a bold technical direction, and partner deeply with the robot-arm and industrial-automation ecosystem to make NVIDIA the default platform for robotic manipulation.
What you'll be doing:
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.
What we need to see:
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.
Ways to stand out from the crowd:
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.
Manipulation is one of the defining unsolved problems in robotics, and NVIDIA is uniquely positioned - across simulation, foundation models, and accelerated compute - to solve it at platform scale. You'll lead a team that the entire robotics industry builds on, and your work will show up on factory floors and in warehouses around the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About Nvidia
Sourced by ZipRecruiter
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Santa Clara, CA, US
Year founded
1993