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Data Architect, Robotics
Mind Robotics · Palo Alto, California, United States
Pay
$115k–200k
Setting
On-site
Listed by Mind Robotics for a position based in the United States. Employers on this board attest they are hiring domestically.
Robotics Software Engineer
Mind Robotics · Palo Alto, California, United States
Pay
$140k–205k
Setting
On-site
Robotics Software Engineer
Location
Palo Alto
Employment Type
Full time
Location Type
On-site
Department
Software Engineering
Overview
Application
About Mind:
Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.
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. Delivering this in production requires robust, high-performance robotics software that can reliably operate in complex, real-world settings.
We’re looking for a Robotics Software Engineer to build the runtime systems, middleware, and developer infrastructure that power our robotic platforms—from low-level execution to operator-facing tools.
Responsibilities:
Design, develop, and maintain runtime systems that enable reliable, low-latency operation of robotic platforms.
Ensure robustness of robotics systems across real-world deployment scenarios.
Implement and optimize robotics middleware for inter-process communication, data serialization, and message passing.
Integrate with frameworks like DDS, Zenoh, or build custom solutions as needed.
Build systems for task scheduling, resource management, and lifecycle management of robotic applications.
Enable scalable and modular execution of complex robotic behaviors.
Ensure that robotics systems meet strict latency and reliability requirements.
Optimize for resource-constrained and embedded environments.
Develop tools to monitor system health, debug failures, and analyze performance.
Design and maintain deployment workflows, CI/CD pipelines, and containerization (e.g., Docker).
Build abstractions, APIs, and tools that enable application engineers to develop robotic behaviors efficiently.
Contribute to operator-facing tools (e.g., UI for monitoring, control, and data annotation workflows).
Focus on developer experience and system ergonomics, ensuring that the platform scales across robots, tasks, and environments.
Requirements:
Strong experience building robotics software systems and middleware.
Experience designing and building runtime systems, execution frameworks, or middleware layers.
Strong understanding of distributed systems and communication patterns in robotics.
Experience working with real-time constraints and performance-critical systems.
Strong proficiency in Python programming.
Familiarity with robotics middleware frameworks (e.g., DDS, Zenoh, ROS2).
Experience with containerization, CI/CD, and codebase management at scale.
Ability to design clean abstractions and APIs for internal users.
Experience building tools or interfaces for operators or engineers.
Nice to Have:
Background in building operator tools or robotics UIs.
Experience supporting ML-driven robotic systems.
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Listed by Mind Robotics for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Engineer
Mind Robotics · Palo Alto, California, United States
Pay
$95k–320k
Setting
On-site
Research Engineer
Location
Palo Alto
Employment Type
Full time
Location Type
On-site
Department
Software Engineering
Overview
Application
About Mind:
Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.
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 ability to iterate quickly on large-scale models depends on world-class ML infrastructure.
We’re looking for a Research Engineer to build the core systems that enable fast, reliable, and scalable model training—powering everything from experimentation to production deployment.
Responsibilities:
Design and implement scalable systems for training large ML models.
Enable efficient workflows for data ingestion, training, and iteration.
Develop and optimize distributed training systems across hundreds of GPUs.
Implement strategies for parallelization, sharding, and efficient compute utilization.
Improve training efficiency through techniques such as attention optimizations, kernel fusion, and memory management.
Partner closely with modeling teams to accelerate iteration speed and reduce training costs.
Build internal tools for experiment tracking, monitoring, and debugging.
Implement systems for tracking training performance, failures, and resource utilization.
Debug and resolve bottlenecks across the training stack.
Provide lightweight infrastructure support for deploying and running models in production environments.
Optimize inference performance and reliability where needed.
Support core cloud infrastructure needs for training workloads (without heavy DevOps overhead).
Manage compute resources efficiently across training jobs.
Requirements:
Strong experience building infrastructure for large-scale ML training.
Deep understanding of how modern LLM/VLM systems are trained and scaled.
Proven experience setting up and scaling distributed training across hundreds of GPUs.
Strong understanding of parallelization strategies (data, model, pipeline parallelism).
Strong proficiency in Python programming.
Expert-level proficiency in PyTorch and/or JAX.
Strong understanding of techniques like attention optimization, kernel fusion, and efficient memory usage.
Nice to Have:
Experience supporting inference systems in production.
Familiarity with robotics or embodied AI workloads.
Experience building tools for experiment management and researcher productivity.
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Listed by Mind Robotics for a position based in the United States. Employers on this board attest they are hiring domestically.
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