Robotics Engineer

Robotics Engineer – Robotics Data & ML Systems

Location: Onsite (Phoenix, AZ)

Employment Type: Full-Time

Objectways is building large-scale robotics data pipelines to support learning-based manipulation systems. We are looking for a full-time Robotics Engineer who can own and execute the data validation, dataset design, and evaluation workflows required to ensure our robotics data is correct, structured, and scalable.

This role sits at the intersection of robotic manipulation, data engineering, and ML evaluation
. You will be responsible not just for running robots, but for ensuring that the data we collect is fit for downstream training and decision-making
.

If you enjoy building things correctly before scaling, this role is a strong fit.

• Design, review, and improve robotics lab setups for manipulation tasks
• Work with robotic platforms (arms, grippers, sensors) to ensure reliable data capture
• Own end-to-end workflows across:
• Robot control
• Sensor and vision capture
• Data storage and pipelines
• Ensure data collection setups are repeatable, debuggable, and scalable

• Define structured episode formats for robotic manipulation tasks
• Design dataset schemas covering:
• Task definitions
• Metadata
• Environment and variation dimensions
• Standardize data collection practices across operators and setups

• Build and maintain data validation and evaluation pipelines
• Define metrics, pass/fail criteria, and reporting formats
  
  Use or integrate with open-source robotics ML frameworks (e.g., LeRobot, OpenPI, PyTorch-based stacks)
  Run baseline evaluations to verify data usability for training

• Document findings, risks, and recommendations clearly
• Identify issues early that could impact scaling or model performance
• Work closely with internal teams and partners to refine data strategy

• 1–3+ years of experience in robotics engineering or robotic manipulation

Hands‑on experience with:

• Robot arms and end-effectors
• Vision-based manipulation systems
• Robotics data collection for ML / RL

Strong understanding of:

• Dataset and episode design
• Data quality and validation for ML systems
• Differences between validation-scale and production-scale systems
• Experience with Python and modern robotics / ML tooling
• Ability to write clear technical documentation and internal reports

• Experience with imitation learning or reinforcement learning
• Familiarity with robotics data scaling challenges
• Exposure to open-source robotics ML frameworks
• Cloud experience (AWS, GCP, or Azure) for data pipelines

• Work on real-world robotics data problems
  , not just simulations
• Own foundational decisions that affect downstream ML performance
• Collaborate with robotics partners and customers building next-generation systems
• Long-term opportunity to grow into a technical leadership role in robotics data and ML systems