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Mid-Level Computer Vision Engineer

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Tristar AI
Full Time position
Listed on 2026-05-25
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

At Tristar AI, we are transforming manufacturing by bringing cutting-edge computer vision tools

to the factory floor. Our focus is on empowering frontline operators and managers whether the customer is a family-run plastics factory or a global automotive titan. Born out of research at MIT and Harvard, we are headquartered in Cambridge, MA, serving customers across North America. Founded in 2021, we are backed by world-class investors and partners, including some of the earliest investors in Cruise, Ring, Dropbox, and more.

This is an incredible opportunity to join on the ground level of a rapidly growing startup. The features you build here will be used every day by leading manufacturers. You’ll have the opportunity to work in a fast-paced environment and shape the future of the company and its technology. You will report to Tristar AI’s Head of Engineering. This is a hybrid role based out of our Kendall Square office in Cambridge, MA

About You
  • You love a good challenge and learning new things.
  • You’re able to own a core part of the product and juggle the different requirements that come along with it.
  • You are comfortable moving around a technology stack to understand how different features work and contribute to different parts of the platform.
  • An entrepreneurial spirit and eagerness to try new things and be innovative.
  • A bias for action, a roll-up your sleeves attitude, and a deep sense of personal ownership.
Responsibilities
  • Develop and implement machine learning models and algorithms for computer vision applications in manufacturing.
  • Conduct research, experimentation, and prototyping to enhance the accuracy and efficiency of computer vision systems.
  • Train, fine-tune, and optimize machine learning models to handle a variety of manufacturing tasks, such as quality control, defect detection, object recognition, and process optimization.
  • Create robust, scalable, and production-ready code for deployment of machine learning models on manufacturing lines.
  • Keep up-to-date with the latest advancements in machine learning and computer vision technologies and bring innovative ideas to the team.
  • Collaborate with customers to understand their unique manufacturing challenges and tailor solutions to meet their specific needs.
Qualifications
  • MS/PhD degree in Machine Learning, Computer Science, Software Engineering, Data Science or related fields preferred (open to BS with relevant professional and/or academic experience)
  • Experience developing computer vision software for manufacturing environments is a
  • 2+ years experience working in computer vision and machine learning
  • Knowledge of machine learning and computer vision libraries such as PyTorch, YOLO,
  • Proficiency in unsupervised, and semi-supervised learning techniques
  • Proficiency with autoencoder is a good plus to have
  • Proven research or practical experience in developing algorithms for image processing, content-based video/image analysis, object detection, segmentation and tracking
  • Familiar with version control systems such as Git
  • Strong optimization and debugging skills

    Experience using traditional computer vision techniques
Benefits
  • Direct impact on product and culture
  • Company equity
  • Competitive compensation and benefits
  • Free coffee, juice, and snacks at our CIC office in Cambridge
  • Sponsored company events and happy hours

We are an equal-opportunity employer. At Tristar AI, we celebrate all. Qualified applicants will

receive consideration for employment without regard to race, religion, color, national origin,

gender, sexual orientation, age, marital status, veteran status, or disability status. Help us build

an inclusive community that will transform frontline operations.

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