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Ixian Robotics

Designs and builds intelligent manufacturing robots

Robotics Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Experience training deep learning models and explaining the decisions behind experiments.
  • Strong Python skills and practical proficiency with PyTorch, JAX, or an equivalent framework.
  • Depth in robot learning or a closely related area, such as computer vision, multimodal learning, or sequential decision-making.
  • Careful experimental judgment, including useful baselines, meaningful comparisons, and understanding what limited evaluation data can establish.
  • Ability to debug training code, inspect datasets, and work directly with physical systems to test conclusions.

Responsibilities

  • Train and fine-tune models for robotic perception and behavior, selecting approaches suited to the task and available data.
  • Turn research ideas into working implementations and compare architectures and training methods through controlled experiments.
  • Curate datasets, investigate data quality, and measure how changes in training data affect performance.
  • Build evaluations with clear success criteria, repeatable procedures, and regression tracking across model versions.
  • Run models on physical robots, inspect failures, and work with engineering teams to improve reliability.
  • Maintain reproducible training workflows, including data loading, experiment tracking, and efficient use of compute.

Desired Qualifications

  • Experience deploying learned policies on robots.
  • Experience with imitation learning, reinforcement learning, or vision-language-action models.
  • Experience with distributed training or building evaluation infrastructure.

About the Company

Ixian Robotics

Designs and builds intelligent manufacturing robots

Ixian Robotics designs and builds intelligent robots intended to bolster domestic manufacturing in the United States. Its products focus on physical robotic systems that can automate factory tasks, combining sensors, control software, and mechanical hardware to operate in industrial environments. The company differentiates itself by targeting real-world manufacturing capabilities and hiring engineers to build tangible hardware systems, rather than software-only solutions, and by positioning itself as a driver for reindustrialization. Its goal is to expand U.S. manufacturing capacity through scalable robotic automation, backed by notable investors after emerging from stealth in 2026.

Company size
Not listed
Company stage
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Total funding
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Headquarters
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Founded
2026

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