Research + Modeling
Join Mind Robotics as a Research & Modeling Engineer to build and train core models for real-world robotic systems.
Posted by employer 9 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 17 hours ago
Skills & Technologies
AI in the day-to-day
null
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
In the Research & Modeling role at Mind Robotics, the engineer is responsible for designing and executing large-scale training pipelines for multimodal systems, ensuring that models translate effectively into robotic actions. Key skills include expertise in machine learning, particularly in building and training large-scale models, as well as proficiency in Python and experience with distributed systems. This position is ideal for someone with a strong background in robotics or related fields, who is comfortable working hands-on with robots to refine their performance. Mind Robotics emphasizes a collaborative environment where innovative problem-solving is essential for advancing physical AI
Joblaze insights
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Machine Learning, Python, Robotics, VLA systems.
- What seniority level is this role?
- Mind Robotics targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research + Modeling role at Mind Robotics.
From the original posting
About the team and the role:
At Mind Robotics, we’re building generalized physical AI—robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. Our models sit at the core of this effort, bridging cutting-edge foundation model techniques with real-world robotic execution.
We’re looking for a Research & Modeling Engineer to build and train the core models that power our systems, and ensure they perform reliably on real robots in production environments.
Responsibilities:
Design and run large-scale training pipelines for multimodal / VLA systems.
Own the full loop: data → training → evaluation → deployment on real robots.
Develop scalable infrastructure for data ingestion, training, and iteration.
Translate model outputs into reliable, high-performance robotic actions.
Work hands-on with robots to debug, iterate, and improve behavior.
Define data strategy (quality, scale, diversity) and evaluation frameworks.
Continuously improve performance across real-world tasks and environments.
Requirements:
Built and trained large-scale models (LLMs, VLMs, or robotics foundation models).
Deep understanding of modern ML, training dynamics, and optimization at scale.
Experience with distributed systems and data pipelines for large-scale training.
Comfortable operating end-to-end: from data → model → real-world deployment (including robots).
Domain strength in at least one: robotics, VLA systems, or training LLMs/VLMs from scratch.
Strong Python proficiency.
Nice to Have:
Experience with dexterous manipulation or complex robotic tasks.
Experience deploying models in real-world, production environments.
Standard company text repeated across Mind Robotics's postings is omitted here.