Quick Overview
Job Description
Description
Join our team, dedicated to advancing the state of the art in robotic learning and foundation models. As an AI Engineer in Automation and Robotics, you will be at the forefront of creating, deploying, and maintaining AI and machine learning models, specifically supporting Embodied AI and Robotics research.
Typical Day in the Role
Start your day by integrating a new simulation or robotic arm with our robotic learning framework, adapting our server/client code to the new API. Collect and convert demonstrations in that environment into the correct format for training a model. Conclude your day by launching fine-tuning runs of our internal VLAs and baseline external VLAs, ready for evaluation the next day.
Job Responsibilities
- Fine-tune and improve a variety of sophisticated software implementation projects.
- Architect, design, and implement test automation infrastructure.
- Develop training and evaluation pipelines using Azure Machine Learning.
- Analyze and refine training datasets for robotic and AI applications.
- Develop tools for fast deployment of algorithms in simulation and on hardware.
- Integrate robotic control and perception stacks with simulation frameworks.
Qualifications
- Master''s degree in a technical field such as computer science, computer engineering, or related field required.
- 5-7 years of related experience required.
- Solid foundation in computer science, with strong competencies in data structures, algorithms, and software design.
- Experience with simulation environments or robotic hardware.
- Experience in-depth troubleshooting and unit testing with both new and legacy production systems.
- Proficiency in programming and experience with problem diagnosis and resolution.
- Background in machine learning frameworks such as TensorFlow or PyTorch.
Performance Measurement
Your performance will be measured by your impact on research objectives, including developing new features, performing evaluations, and creating documentation. We practice an agile task planning process to collaboratively decide on the duration and priority of tasks, making progress and impact clear to both parties.
Top 3 Must-Have Skills
- Python – 5 years
- PyTorch – 2 years
- ROS2 – 1 year
Ideal Candidate Background
The ideal candidate is familiar with training robotic models such as vision-language-action models, diffusion models, and reinforcement learning policies. Familiarity with either simulation environments or robotic hardware is necessary for system integration.
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