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UnitX

Machine Learning Engineer

Milpitas, California, United States

Location
Milpitas, California, United States
Work
On-site
Employment
Full-time
Level
Mid level
Function
Data & AI
Pay
$160K – $180K a year
Posted
6 months ago

Pay and the market here

The top of this role’s range, $180K a year, is 14% below the median of $210K for mid level data jobs in California (middle half $170K – $258K, 278 jobs that state pay).

6 data jobs open in Milpitas: 0% remote, 1 posted in the last 30 days.

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About the role

About Us

UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality.

Join us for the rare opportunity to work on computer-vision-driven products that go beyond the state of the art and that improve global manufacturing efficiency.

What You'll Do

  • You will develop new algorithms that consume raw sensor data input to detect defect segmentation and location information on high-resolution images or 3D inputs, with pixel-level precision.
  • You will engineer software that runs on the production line 24/7 to efficiently execute our algorithms in real time with each decision made under 20ms.
  • You will develop metrics and tools to evaluate various model performance and improve visibility and interpretation of our system.
  • You will explore new solutions and push the boundaries of the field including using Stable Diffusion, SAM and build applications for critical missions in the manufacture fields.

Who You Are

  • Bachelor's degree in Computer Science, Mathematics, Physics, or a relevant technical field, or equivalent practical experience. Solid foundational and applied math knowledge.
  • 2+ years of experience in building machine learning models for computer vision in production.
  • Strong theoretical background and practical experience in Deep Learning, with proficiency in PyTorch or Tensorflow. Excellent Python skills for writing efficient and maintainable solutions in large code bases.
  • Strong communication and decision-making skills. Ability to explain the rationale behind experiments and make decisions to balance exploration and exploitation.
  • Resilience in uncertain and complex environments.

Preferred Qualifications

  • Master’s degree in Computer Science, Mathematics, Physics, or a relevant technical field.
  • Experience with model inference optimization
  • Experience with non-ML CV algorithms

Why Join UnitX

This role offers the opportunity to accelerate human productivity through robotics in manufacturing. You get to define how a differentiated AI-vision platform enters some of the world’s fastest-growing and most strategically important manufacturing markets. You will work directly with company leadership, influence product and market strategy, and build relationships that can become significant global accounts.

UnitXis proud to be an Equal Opportunity Employer. We value diversity, inclusion, and respect, and are committed to building a workplace where everyone can thrive. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

We are committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. If you require assistance, please contact Human Resources. Requests for accommodation will be treated confidentially and in accordance with applicable laws.

As a safety-sensitive, drug-free workplace, employment with UnitX is contingent upon successful completion of applicable pre-employment screening requirements.

Source

Posted by UnitX on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 11:57 UTC; the original is the reference.

View the original ad ↗

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