Machine Learning / Reinforcement Learning Engineer
Join Eka Robotics as a Machine Learning Engineer to develop cutting-edge algorithms for robotic manipulation in a fast-paced startup environment.
Posted by employer 1 year ago
First seen on Joblaze 55 minutes ago
Last verified on the company career page 55 minutes ago
What you'll build
- Research and implement reinforcement learning and supervised learning algorithms
- Design simulation models and domain randomization strategies
- Design experiments to evaluate and optimize model architectures
- Develop scalable data management pipelines
- Deploy, evaluate, and debug policies on physical hardware
Must have
- BS, MS, or PhD in Computer Science, Robotics, or a related field
- Deep theoretical and practical knowledge of reinforcement learning and supervised learning algorithms
- Experience with physics engines and robotics middleware
- Expert-level Python skills
- Proficiency in deep learning frameworks
Nice to have
- A history of publications in top-tier robotics or machine learning conferences
- Experience with modern architectures, including Transformers and CNNs
Requirements
- Education
- Bachelor's degree
Not disclosed in this posting: compensation, seniority, years of experience, work arrangement, visa sponsorship.
Joblaze summary
The Machine Learning / Reinforcement Learning Engineer at Eka Robotics focuses on developing and implementing algorithms for robotic manipulation, while also designing simulation models and optimizing performance under real-time constraints. Key skills include a strong foundation in reinforcement learning, experience with physics engines, and proficiency in Python and deep learning frameworks like PyTorch. This role is suited for individuals with advanced degrees in relevant fields and a proven track record in robotics or machine learning research. Eka Robotics emphasizes collaboration within a pioneering team dedicated to advancing robotics technology.
Joblaze insights
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Isaac Sim, JAX, MuJoCo, PyBullet, PyTorch, Python.
- Is this full-time or contract?
- Full-time for this Machine Learning / Reinforcement Learning Engineer role at Eka Robotics.
From the original posting
Responsibilities
Algorithm Development: Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.
Simulation: Design simulation models and domain randomization strategies; collaborate with the robotics team to ensure alignment with physical systems.
Performance Optimization: Design experiments to evaluate and optimize model architectures for sample complexity and policy performance with real-time execution constraints.
Data & Pipeline Engineering: Develop scalable data management pipelines for real and synthetic data; evaluate and select algorithms that maximize data efficiency and overall policy performance.
On-Robot Evaluation: Deploy, evaluate, and debug policies on physical hardware; identify bottlenecks and implement improvements in collaboration with the robotics team.
Qualifications
Education: BS, MS, or PhD in Computer Science, Robotics, or a related field.
Core Expertise: Deep theoretical and practical knowledge of reinforcement learning and supervised learning algorithms.
Robotics Toolkit: Experience with physics engines (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).
Architectural Depth: A deep understanding of modern architectures, including Transformers, CNNs, and Foundation Models.
Technical Proficiency: Expert-level Python skills and proficiency in deep learning frameworks such as PyTorch or JAX.
Engineering Rigor: A strong commitment to clean code, version control, and reproducible experimental workflows.
Track Record: A history of publications in top-tier robotics or machine learning conferences, or a portfolio of projects providing strong practical evidence of expertise in the field.
Standard company text repeated across Eka Robotics's postings is omitted here.
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