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Posted Apr 22Machine Learning Research Engineer
at Roboflow
Remote
Responsibilities
- Build with Roboflow Phase: - You will build a small project with Roboflow to showcase your creativity and technical skills.
Requirements
- We’re building the tools, community, and resources needed to make the world programmable with artificial intelligence.
- Today, over 1M+ developers, including those from half the Fortune 100, use Roboflow’s machine learning open source and hosted tools.
- WHAT YOU'LL DO As a Machine Learning Research Engineer, you will develop novel machine learning methods and contribute to the research agenda of the team.
- You have high agency and a bias toward action. - Masters / PhD in AI, machine learning, computer vision, robotics, or similar technical field of study, or equivalent industry
- experience with both optimizing models for edge hardware and training models on distributed infrastructure - Expertise in PyTorch WHERE YOU'LL WORK Roboflow’s team is distributed across the world.
- 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.
Benefits
- Roboflow simplifies building and using computer vision models.
- 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.
- WHO YOU ARE You are a pragmatic, experienced machine learning researcher who wants to be an important part of an exceptional team that focuses on using Roboflow's computer vision tools to impact and improve every 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) Preferred but not required: - Previous
- You can work from one of our Hubs (we offer a relocation bonus), work from home, work at co-working spaces, etc. We want you to work where you work best! WHAT YOU'LL RECEIVE To determine your salary, we use a number of market and data-driven salary sources.