About the job
About Us
Valo Health is a pioneering biotechnology firm driven by a human-centric and AI-enabled approach, focused on expediting the drug development process for patients. Our innovative Opal Computational Platform revolutionizes drug discovery through an exceptional fusion of real-world data, artificial intelligence, human translational models, and predictive chemistry.
Our dedicated team comprises biologists, chemists, and engineers who leverage advanced AI/ML tools to dismantle traditional research and development silos, thus accelerating the pace and scalability of drug discovery and development.
At Valo, we are devoted to cultivating a diverse workforce, emphasizing professional growth and development, fostering an inclusive workplace, and creating opportunities for collaboration among individuals with varied experiences, backgrounds, and perspectives. We embrace innovative learning methodologies, tackle complex challenges, and welcome diverse viewpoints to advance patient-focused innovations.
Headquartered in Lexington, MA, Valo also operates offices in New York, NY, and Tel Aviv, Israel. To discover more, visit www.valohealth.com.
About The Role
Valo is seeking an accomplished Senior Machine Learning Engineer to design and implement groundbreaking AI solutions to enhance computationally accelerated drug development initiatives. You will enhance the functionality of Valo’s Opal platform to support real-world, active drug development programs. The ideal candidate will thrive in a diverse team comprising scientists, software engineers, data scientists, and domain experts, working collaboratively across traditional industry boundaries within a dynamic startup environment.
What You’ll Do...
- Design, develop, test, maintain, and improve an integrated codebase of AI and machine learning tools.
- Collaborate with data scientists, researchers, product teams, and other domain experts to devise solutions for intricate data-oriented challenges.
- Create solutions to advance real-world preclinical discovery programs, addressing issues such as ADME modeling, toxicity prediction, and generative chemistry.

