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Machine Learning Engineer

UnitX

UnitX

Software Engineering
USD 160k-180k / year + Equity
Posted on Apr 4, 2026

Location

HQ

Employment Type

Full time

Location Type

On-site

Department

Software

Compensation

  • $160K – $180K • Offers Equity

Job Title:

Machine Learning Engineer

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

Compensation & Benefits

  • Competitive cash and equity

  • Full Medical, Dental, Vision, 401k

  • Unlimited PTO

  • Daily meals provided

Compensation Range: $160K - $180K