Machine Learning Research Engineer

Role Description

As a Machine Learning Research Engineer, you will develop novel machine learning methods and contribute to the research agenda of the team. Because of Roboflow’s huge userbase, we have a unique visibility into how people are using computer vision in the real world, including in what circumstances existing methods are unable to solve user problems.

• Introduce novel methods that generalize across our user base.
• Methods that learn well on diverse data.
• Run efficiently on different hardware targets.
• Solve unique categories of problems.
• Identify areas for innovation.
• Create novel approaches.
• Write papers aimed at top conferences.
• Translate research methods into production systems running at scale.

Qualifications

• Masters / PhD in AI, machine learning, computer vision, robotics, or similar technical field of study, or equivalent industry experience.
• History of publication at conferences / journals (CVPR, NeurIPS, ICLR, etc.).
• Proficient in Python.
• Values scientific rigour, reproducibility, and high quality software.
• Passionate about computer vision and solving problems users value.
• Pragmatic approach to utility in practice (not just in theory).

Requirements

• Previous experience with both optimizing models for edge hardware and training models on distributed infrastructure (preferred but not required).
• Expertise in PyTorch (preferred but not required).

Benefits

• $4000/yr Travel Stipend to travel anywhere anytime to work alongside other Roboflowers.
• Cover up to 100% of your health insurance costs for you and your partner or family.
• $350/mo Productivity stipend to spend on things that make your work environment more productive, like high-speed internet at home or a co-working space.
• $350/mo AI Stipend.
• $500 one time home office stipend.
• $150/mo Team lunch stipend.
• Unlimited PTO - with an annual 2 week minimum, we encourage you to take time off for yourself.
• 12 weeks parental leave.
• Equity in the company so we are all invested in the future of computer vision.

Interview Process

Below is the interview process you can expect for this role. We’re committed to building an exceptional team and aim to be thoughtful while also moving quickly. We respect your time and strive to make decisions efficiently, depending on scheduling and availability.

• Several conversations with the hiring manager, a member of the Roboflow leadership team, and complete a role-relevant project or challenge.
• Introduction Phase:
  • [30m] Meet with hiring manager to assess for overall mindset and skillset.
  • [1h30m] Technical Assessment:
    • Prior Research Deep Dive.
    • Software Fundamentals.
    • Math Question.
• Team Interview Phase:
  • [30m] Meet with another member of the team.
  • Build with Roboflow Phase:
    • Build a small project with Roboflow to showcase your creativity and technical skills.
    • [30m] Meet with our CTO, Brad Dwyer, for another interview and to demo your project.
• Final Interview Stage:
  • [60m] Meet with hiring manager again to review specifics about the job description and begin working through your 30/60/90 projects.
  • [30m] Leadership conversation focused on culture and company vision (if needed).
  • [30m] Additional leadership discussion to discuss culture.

References

References are required as part of our process. We will reach out to coordinate timing.

Note: you are welcome to request additional conversations with anyone you would like to meet and we will accommodate as best we can.

Not sure if this is you?

We want a diverse, global team with a broad range of experience and perspectives. We carefully consider every application and will either move forward with you, find another team that might be a better fit, keep in touch for future opportunities, or thank you for your time.

Learn More About Us

At Roboflow, we believe great ideas come from everywhere, and everyone. We’re proud to be an Equal Opportunity Employer committed to building a diverse and inclusive team. We consider all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, or any other legally protected characteristics.