Senior Machine Learning Engineer

Valo Health•Lexington, MA

2d•$153,000 - $212,400•Remote

About The Position

Valo is looking for an experienced Senior Machine Learning Engineer to design and implement novel AI solutions to advance computationally accelerated drug development programs. You will develop, apply and enhance the capabilities of Valo’s Opal platform to advance real-world, active drug development programs. Successful candidates must be committed to working with a diverse set of scientists, software engineers, data scientists, and domain experts in ways that cut across traditional industry boundaries in a fast-paced startup environment.

Requirements

A PhD (or Master’s with experience) in Computer Science, Data Science or related technical field
Two years of experience applying modern ML/AI techniques to real-world problems with demonstrated business impact
Strong proficiency in python and modern ML frameworks (PyTorch, Hugging Face)
An aptitude for learning about new domains and adapting machine learning techniques to impact drug discovery
Experience with software engineering best practices and an ability to write clean, re-usable code in a collaborative environment
Experience and interest contributing to all stages of ML development and deployment
Strong analytical, problem-solving, and communication skills, including the ability to also condense, summarize, and synthesize those results into informative and actionable presentations to less technical audiences.
Strong personal project management skills with demonstrated ability to deliver iterative results and balance tradeoffs between exploratory research and delivering short-term value
At this time, we are only able to consider candidates who currently have permanent US work authorization without the need for immediate or future sponsorship.

Responsibilities

Design, develop, test, maintain, and improve an integrated codebase of AI and machine learning tools
Work with data scientists, researchers, product teams, and other domain experts to build solutions for complex data-oriented problems
Develop solutions for advancing real-world preclinical discovery programs, tackling problems such as ADME modeling, toxicity prediction, and generative chemistry.