Machine Learning Engineer
Milpitas, California, United States On-site
$160,000–$180,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
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
What you'll bring
- 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.
- Master’s degree in Computer Science, Mathematics, Physics, or a relevant technical field.
- Experience with model inference optimization
- Experience with non-ML CV algorithms