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Open nowPosted 585 days ago

Machine Learning / Reinforcement Learning Engineer

Eka8 open roles

Where
Boston Area
Work mode
On site
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Your applicationOpen nowMachine Learning / Reinforcement Learning EngineerEka · Boston Area

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

9.0% of postings close within 7 days. Measured by our own scanner across the market. Eka postings stay open a median of 13 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.9%3 days
  3. 9.0%7 days
  4. 15.5%14 days
  5. 34.0%30 days
This job: posted 585 days ago

Eka median: 13 days open

The posting

Eka Robotics

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Our approach, grounded in physics, unlocks superhuman capabilities. We are defining the frontier of robotics research and deployment.

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D effort. We are looking for hands-on individuals who are excited to help shape the future of robotics.

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.

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