Research Scientist
- BC, Canada
- British Columbia, Canada, Canada
Full-time
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Job details
- Job type
- Full-time
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- Posting language
- English
- Posted
Original job description
Research Scientist – Robotics & Machine Learning
Up to $300k + equity
The Opportunity
An innovative robotics company is seeking a Staff Research Scientist to advance reinforcement learning, imitation learning, and dextrous manipulation.
As a Research Scientist, you will work at the intersection of machine learning research and real-world robotics, developing algorithms that enable robots to perform increasingly complex physical tasks. You will help shape research direction, build scalable training and data collection pipelines, evaluate algorithms in simulation, and deploy models onto physical robotic systems.
This Research Scientist position offers significant technical ownership, from exploring novel learning approaches to translating research breakthroughs into practical robotic capabilities.
What's in It for You?
- Up to $300k + Stock Options – Competitive compensation with equity participation.
- Exceptional Team – Work alongside leading researchers and engineers with strong academic backgrounds in AI, ML, and robotics.
- Cutting-Edge Research – Apply advanced RL/IL techniques to real-world robotic manipulation.
- Technical Ownership – Shape research direction and take projects from concept to deployment.
- Real-World Impact – Help push the boundaries of intelligent robotics and next-generation AI.
Key Responsibilities
- Research, develop, and optimise reinforcement learning (RL) and imitation learning (IL) algorithms for complex robotic manipulation tasks.
- Evaluate emerging research methods and translate promising techniques into practical robotic applications.
- Improve learning efficiency, training speed, computational performance, and scalability across RL/IL workflows.
- Design and implement scalable training, simulation, and data collection pipelines to accelerate deployment on physical robots.
- Investigate algorithm performance, diagnose failure modes, and develop robust solutions to complex technical challenges.
Experience & Qualifications
- PhD in Machine Learning, Computer Science, Applied Mathematics, Robotics, or a related discipline, or equivalent practical research experience.
- 3+ years of hands-on experience developing and deploying robotic manipulation capabilities in simulation and on physical robots.
- 3+ years of practical experience applying reinforcement learning and/or imitation learning, ideally in real-world robotics applications.
- Strong understanding of sim-to-real transfer techniques and the challenges of deploying learned policies onto physical hardware.
- Experience integrating machine learning models into robotic platforms and validating their performance in real-world environments.
- A strong research track record, including publications at leading robotics and machine learning conferences such as ICRA, IROS, CoRL, or equivalent venues.
Technical Skills
- Dextrous Manipulation Expertise - Experience developing learning-based approaches for complex robotic manipulation and fine motor control in real-world environments
- Strong Python development skills.
- Practical experience with PyTorch and/or TensorFlow.
- Familiarity with ROS 2 and robotics software architectures.
- Deep understanding of reinforcement learning & imitation learning
- Experience with collaborative development tools such as Git, Jira, Confluence, GitLab, or equivalent platforms.
Interested in Learning More?
If your background combines reinforcement learning, imitation learning, and hands-on robotic manipulation, get in touch for a confidential discussion about this Research Scientist opportunity.
More about this job
Responsibilities
Develop and optimize reinforcement and imitation learning algorithms for complex robotic manipulation, evaluating research methods and improving learning efficiency, training speed, performance, and scalability. Build training, simulation, and data collection pipelines, diagnose algorithm failures, and deploy and validate learned models on physical robots.
Requirements
Requires a PhD in machine learning, computer science, applied mathematics, robotics, or a related field, or equivalent practical research experience, plus at least three years developing robotic manipulation capabilities in simulation and on physical robots. Candidates should have practical reinforcement or imitation learning experience, sim-to-real and hardware deployment expertise, a strong research publication record, and proficiency with Python and relevant ML and robotics tools.
Skills
- Reinforcement Learning
- Imitation Learning
- Robotic Manipulation
- Dextrous Manipulation
- Python
- PyTorch
- TensorFlow
- ROS 2
- Sim-to-Real Transfer
- Robotics Software Architectures
- Simulation
- Data Collection Pipelines
- Model Deployment
- Git
- Jira
- GitLab
Benefits
- Stock Options
Visa sponsorship
Not detected in the job text
Categories
- Science & Research
- Engineering
- Technology
- Software
Keywords
- Reinforcement Learning
- Imitation Learning
- Robotic Manipulation
- Dextrous Manipulation
- Machine Learning
- Robotics
- Python
- PyTorch
- TensorFlow
- ROS 2
- Sim-to-Real Transfer
- Physical Robots
- Robotic Platforms
- Simulation
- Training Pipelines
- Data Collection
- Model Deployment
- Algorithm Evaluation
- Fine Motor Control
- Computational Performance
- Scalability
- Research Publications
- ICRA
- IROS
- CoRL
- Git
- Jira
- Confluence
- GitLab