Production Vision ML Engineer - On-Site, Equity

UnitX; Santa Clara (CA); On-site; Full time

Job description

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