Senior Software Engineer; Robotic Packing​/Manipulation

• As part of the Core software team, you will develop learning-based approaches that help robots reason about 3D environments, anticipate the outcomes of physical interactions, and make effective decisions over sequences of actions
• The work combines perception, planning, and manipulation, with an emphasis on reliable performance under uncertainty and real-world constraints
• You’ll explore both data-driven and model-based approaches, evaluate them in simulation, and bring promising methods onto physical robotic systems
• Your work will contribute to enhancing the capabilities of our robotic solutions and explore new solutions and approaches, unlocking new value to be delivered to our customers
• This position offers a unique opportunity to work at the cutting edge of robotics applied to real-world challenges
• Develop learning methods for spatial reasoning, sequential decision-making, and robotic manipulation
• Combine learned policies and predictive models with planning and optimization to solve physically constrained tasks
• Design training and evaluation workflows that measure task success, robustness, and execution efficiency
• Quickly prototype solutions, creating demos for stakeholders and visitors
• Serve as subject matter for transitioning prototypes to product teams
• Identify high impact areas for improvements of our robotic systems to solve real problems
• Utilize and extend simulation software environments to develop and test manipulation behaviors
• Stay abreast of the latest advancements in robotics and related fields, evaluating applicability to our challenges
• Collaborate with external research partners to find solutions for BG’s problem space
• Assist with mentorship of more junior engineers or interns
• Communicate technical priorities and status

• Healthcare
  - Full medical, dental and vision. Life insurance, gym stipends and wellness programs
• Vacation
  - We value hard work and we like to have fun. Take time when you need it
• Recognition
  - Peer shout outs, achievement celebrations and leadership awards let you know you’ve made a difference
• Retirement
  - Stock options and generous 401(k) matching
• Nutrients
  - Lunch is delivered daily, a plethora of snacks, gourmet coffee, Soylent, and top-shelf beverages

4+ years of experience in software development with a focus on robotics manipulation or related areas

Experience with data science tools & libraries like numpy, pandas, scipy, matplotlib, scikit-learn

Determine and communicate justification of technical priorities

Experience with major deep learning frameworks such as Py Torch Experience  in working with ROS or ROS2

Strong development expertise in Python and C++Develop on and troubleshoot real robotic systems

Master’s degree in Robotics, Machine Learning, Computer Vision, Computer Science or a closely related field

Strong verbal and written communication skills, capable of explaining complex ideas clearly and concisely to both technical and non-technical stakeholders

Provide technical leadership on key projects

Demonstrated experience training and adapting of existing machine learning architectures for robot learning, to solve tasks in domains such as manipulation, locomotion, or navigation

Work independently on a variety of projects while maintaining focus

Mentor junior engineers

Demonstrated ability to:

Work in a fast-paced environment with changing priorities

Rapidly prototype and iterate on solutions to challenging problems

PhD in Robotics, Machine Learning, Computer Science or a closely related field

Demonstrated technical proficiency in solving spatial reasoning and sequential decision-making in robotics

Applying machine learning to hardware interacting with the real world

Sim-to-real for robotic manipulation

Real and simulated data capture

Real-time perception-based control

Incorporating tactile sensor information into manipulation behaviors

Robot simulators (e.g. OpenRAVE, Isaac Sim or Mu Jo Co )
Robot learning frameworks (e.g. Isaac-Gym, Orbit / Isaac Labs)
Docker, cloud computing, or similar applications

Combining model-based and data-driven approaches

Experiment tracking and dataset management (e.g. Weights & Biases)
Database systems as data source, such as MongoDB Parallel/distributed systems and asynchronous/concurrent programming

Knowledge of LLM usage within robotics context