What are the responsibilities and job description for the Staff Machine Learning Infrastructure Engineer position at Dyna Robotics?
Company Overview :
Dyna Robotics is at the forefront of revolutionizing robotic manipulation with cutting-edge foundation models. Our mission is to empower businesses by automating repetitive, stationary tasks with affordable, intelligent robotic arms. Leveraging the latest advancements in foundation models, we're driving the future of general-purpose robotics-one manipulation skill at a time.
Dyna Robotics was founded by industry leaders who previously achieved a $350 million exit in grocery deep tech as well as top robotics researchers from DeepMind and Nvidia. Our team blends world-class research, engineering, and product innovation to drive the future of robotic manipulation. With $20mil in funding, we're positioned to redefine the landscape of robotic automation. Join us to shape the next frontier of AI-driven robotics.
Position Overview :
We are seeking an experienced Machine Learning Infrastructure Engineer to join our team and help scale our ML training platform. In this role, you will be responsible for designing, implementing, and maintaining large-scale ML infrastructure to accelerate model iteration and improve training performance across an expanding GPU ecosystem. You will work on cutting-edge high-performance computing systems, optimizing distributed training environments, and ensuring system reliability as we scale.
Key Responsibilities :
- Infrastructure Design & Scalability :
Architect and implement large-scale ML training pipelines that leverage parallel GPU processing on platforms like GCP or AWS.
Manage and optimize high-performance computing resources.
Design systems for job rescheduling, automated retries, and failure recovery to maximize uptime and training efficiency.
Evaluate and implement tradeoffs between different local and networked storage solutions to improve data throughput and access.
Work closely with ML researchers and data scientists to understand training requirements and bottlenecks.
Required Qualifications :
Preferred Qualifications :
Benefits
If you're passionate about building scalable ML systems and optimizing high-performance computing infrastructures, we'd love to hear from you.
Salary : $20
