Machine Learning Engineer

Tl;dr

Apply the latest ML for code research at a startup backed by Y Combinator and leading VCs, building tools that directly help software engineers.

Background

At bloop, we’re building an in-IDE code search engine to make it easy for software engineers to find and share code. Today developers spend too much time scouring library documentation and open-source repositories looking for useful code. Our neural search engine automates this menial process, freeing up time for developers to focus on the most enjoyable parts of the job. But radically better code search won’t just help individual developers, we believe it will unlock the next level of software collaboration.

Since launching bloop over the summer we’ve introduced thousands of engineers to neural code-search, achieved Product Hunt’s Product of the Day, and raised our seed funding round from leading investors including Y Combinator (S21), Khosla Ventures, Sands Capital and LocalGlobe.

As we head into our next period of hyper-growth, we’re looking to partner with people that are hungry to work at the cutting edge of innovation and research, and directly impact the way tomorrow’s software engineers work.

The Role: Machine Learning Engineer

Machine learning is at the heart of our code search engine. It enables us to retrieve relevant results based on abstract search queries (like parse and XML file) or on the state of a developer’s project. We’re applying techniques from the latest ML-for-code research to learn embedding spaces that improve search results.

As a Machine Learning Engineer you’ll work on bloop’s core search functionality, building a pipeline that enables semantic code search. You’ll:

• Read and implement the latest ML-for-code research
• Evaluate model impact on code search performance
• Deploy the best-performing models to production

Key requirements

• Strong grasp of core ML/NLP concepts
• Proficiency in Python and at least one ML library (ideally PyTorch or JAX)
• Experience deploying ML models (AWS, Kubernetes)
• Ability to communicate technical ideas
• (Bonus) Academic or practical experience with modern IR systems
• (Bonus) Experience training and fine-tuning transformer language models
• (Bonus) Interest in programming language implementation (parsers, compilers)

The deal

• Competitive package
• Our office is in Farringdon, Central London and we'd like to meet as a team in-person at least once per week, although more/less is possible
• Even if you only meet some of the requirements, it's worth applying as we're all from non-traditional backgrounds and are open minded