高级机器学习工程师 - 强化学习
Senior Machine Learning Engineer - Reinforcement Learning
构建未来路径
在 Path Robotics，我们正在打造具身智能的未来。我们的 AI 驱动系统使机器人能够在现实世界中适应、学习并执行任务，弥合技术劳动力的缺口并改变行业。我们超越传统方法，结合感知、推理和控制，提供可现场部署的 AI，具备风险意识、可靠性和通过实际使用持续改进的能力。
我们每天都在解决大而复杂的问题，由一群聪明、谦逊且有动力的人共同将不可能变为可能。
作为专注于强化学习的高级机器学习工程师，你将设计、实现和优化强化学习算法，使智能体能够在动态、非结构化环境中运行。该职位需要与跨职能团队紧密合作，设计、测试和部署创新解决方案，以提升我们机器人系统的性能和能力。该职位可在我们的俄亥俄州哥伦布总部或远程办公。
你将负责
- 为机器人控制、运动规划和自适应行为设计、实现和评估强化学习算法，在动态、非结构化环境中运行。
- 开发并集成强化学习策略与机器人控制系统，确保与硬件限制和实时需求兼容。
- 与感知团队合作，将强化学习与视觉、深度和传感器数据融合，实现稳健决策。
- 构建和维护仿真到现实的流程，包括领域随机化和迁移学习技术。
- 在实体机器人上进行实验，包括设计安全协议和监控异常行为。
- 利用仿真环境（Isaac Gym、Gazebo、MuJoCo、PyBullet）进行大规模训练，再进行现实验证。
- 持续提高模型效率，使其在嵌入式机器人系统上的计算和延迟限制内运行。
你应具备
- 计算机科学、机器人学、机器学习或相关领域的硕士或博士学历，或同等实践经验。
- 在真实系统上开发和部署强化学习算法的经验。
- 精通 Python 和深度学习框架如 PyTorch 或 TensorFlow。
- 使用仿真环境（例如 MuJoCo、Isaac Gym）的经验。
- 对概率、统计学和优化有扎实的理解。
- 在生产系统中训练和部署机器学习模型的经验。
为什么你会喜欢这里
- 每天免费午餐，让你保持活力和专注
查看英文原文
Build the Path Forward
At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.
Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.
As a Sr.ML Engineer focused on Reinforcement Learning, you will design, implement, and optimize RL algorithms that enable intelligent agents to operate in dynamic, unstructured environments. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems. This role can be located in our Columbus, Ohio Headquarters or Remote.
What You’ll Do
- Design, implement, and evaluate RL algorithms for robotic control, motion planning, and adaptive behaviors in dynamic, unstructured environments.
- Develop and integrate RL policies with robot control systems, ensuring compatibility with hardware constraints and real-time requirements.
- Collaborate with perception teams to fuse RL with vision, depth, and sensor data for robust decision-making.
- Build and maintain sim-to-real pipelines, including domain randomization and transfer learning techniques.
- Conduct experiments on physical robots, including designing safety protocols and monitoring for unexpected behaviors.
- Leverage simulation environments (Isaac Gym, Gazebo, MuJoCo, PyBullet) for large-scale training before real-world validation.
- Continuously improve model efficiency to operate within compute and latency constraints on embedded robotic systems.
Who You Are
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience.
- Experience developing and deploying reinforcement learning algorithms on real-world systems.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Experience with simulation environments (e.g., MuJoCo, Isaac Gym).
- Solid understanding of probability, statistics, and optimization.
- Experience with training and deploying ML models in production systems.
Why You'll Love It Here
- Daily free lunch to keep you fueled and connected with the team
- Flexible PTO so you can take the time you need, when you need it
- Comprehensive medical, dental, and vision coverage
- 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
- 401(k) retirement plan through Empower
- Generous employee referral bonuses—help us grow our team!
Who We Are
At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact . We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.
Originally posted on Himalayas