Machine Learning Research Engineer

Role overview

As a Machine Learning Research Engineer at Roboflow, you will develop novel machine learning methods and contribute to the team’s research agenda. You’ll use Roboflow’s unique visibility into how computer vision is used in the real world to identify where existing methods fail and to drive new approaches that can scale to production.

What you’ll do

• Develop new machine learning research methods and contribute to the research roadmap
• Identify areas for innovation based on real-world user needs and failure modes of existing methods
• Create approaches that generalize across diverse user data
• Ensure methods run efficiently on different hardware targets
• Write research papers aimed at top conferences (e.g., CVPR, NeurIPS, ICLR)
• Translate research work into production systems running at scale

Requirements

• Master’s or PhD in AI/ML/computer vision/robotics (or similar), or equivalent industry experience
• History of publication in conferences/journals such as CVPR, NeurIPS, or ICLR
• Proficient in Python
• Strong commitment to scientific rigor, reproducibility, and high-quality software
• Passion for computer vision and solving user-valued problems
• Pragmatic mindset focused on real utility (not just theory)

Nice to have

• Experience optimizing models for edge hardware and/or training on distributed infrastructure
• Expertise in PyTorch

Work model / location

• Team is distributed worldwide with hubs in New York City, San Francisco, and Brazil
• Work options include working from a hub, remote, and co-working spaces; relocation bonus available and onsite opportunities offered

Compensation

• Target base salary: $168,000–$255,000 (base), depending on location and level