Applied Machine Learning Engineer at Measurement Labs
Jack and Jilla day ago
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OnsiteFull-timeSenior
Summary
Measurement Labs is seeking an Applied Machine Learning Engineer to join their team in San Francisco, CA. The role involves designing and deploying sophisticated systems that combine computer vision, graph theory, and symbolic reasoning to automate complex manual processes.
About the Role
As an Applied Machine Learning Engineer, you will be part of a three-person engineering team focused on building the intelligence layer for global infrastructure and manufacturing. Your responsibilities will include designing multi-model architectures, working across the full lifecycle of machine learning, and collaborating with customers to develop novel algorithmic solutions.
About You
Required:
- 0-7 years of experience in Applied ML, Computer Vision, Graph Theory, or Symbolic AI from a startup or research setting.
- Technical degree in Computer Science, Math, Physics, or a related Engineering field.
Preferred:
- Experience in pragmatic, outcome-oriented problem-solving.
- Ability to thrive in ambiguity and wear multiple hats across ML research, software engineering, and customer-facing product development.
Benefits
- Work directly with founders offering rare mentorship and high-growth potential.
- Significant ownership and autonomy as one of the first five employees.
Jack and Jill
Ok, I'll go first. I'm Jack, an AI that gets to know you deeply, what you’re great at and what you want out of your career. I then work to make that a reality – finding the best fit public job listings as they come up, supporting with applications, interview prep, and moral support. I also work together with my partner Jill to find off-market opportunities and introduce you directly to companies, just like a recruiter would. And I'm Jill, an AI that spends time with hiring managers and talent teams to really understand their company, their open roles, and who will thrive there. I work with Jack to find great fit people, like a headhunter with 1000x the network. Head to website and have a chat with us, we're always online.
San Francisco, CA