Machine Learning Lead

Probably Genetic•San Francisco, CA

3d•Hybrid

About The Position

Probably Genetic is seeking a Machine Learning Lead to run their machine learning (ML) function. This role reports directly to the Chief Technology Officer (CTO). The successful candidate will be the first hire in this new function and will be responsible for building the machine learning team from the ground up. The initial objective of the team will be to develop world-class models to find undiagnosed patients living with severe, complex diseases using a combination of computer vision, large language models (LLMs), classical ML methods, and other technologies. As the company grows, the scope will expand to additional machine learning challenges in healthcare, genetics, and drug development. The role involves developing groundbreaking machine learning systems, shaping and executing the ML strategy in collaboration with the CTO, designing and orchestrating ML experiments, managing a team of ML experts, data scientists, engineers, and bioinformaticians, and working closely with engineering, growth, and business development teams. The role will own key patient finding metrics that directly impact company goals.

Requirements

Advanced degree in Computer Science, Artificial Intelligence, Bioinformatics, or a related field with a strong emphasis on machine learning
Minimum of 8-10 years of experience in machine learning
At least 3-5 years in a leadership role managing teams of data scientists and engineers in a healthcare technology or genomics setting
Deep understanding of statistics and Bayesian modeling
Experience in training deep learning and computer vision models as well as classical ML models
Experience in designing and maintaining robust machine learning pipelines from training and monitoring to deployment, ensuring scalability and reliability
Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders, ensuring alignment and understanding across diverse teams
Experience in managing complex project and experiment timelines with cross-functional dependencies to deliver accurate models on time
A good person with empathy
Patient-focused and motivated to have a lasting, positive impact on humanity
Comfortable in a fast-paced, often ambiguous environment with rapid change
Action-oriented and excited to build a company from the ground up

Nice To Haves

Experience with language model implementation, specifically using LLMs for retrieval-augmented generation (RAG) and complex automation workflows
Expertise in developing and implementing machine learning products for severe, complex disease identification and phenotyping

Responsibilities

Develop groundbreaking machine learning systems to change the lives of patients living with severe, complex diseases
Shape and execute our machine learning strategy in close collaboration with our CTO
Design and orchestrate machine learning experiments to improve the accuracy of our patient identification models
Manage a function consisting of machine learning experts, data scientists, engineers, and bioinformaticians
Work closely with our engineering, growth, and business development teams to ensure our machine learning strategy is tightly integrated into all aspects of the business
Own key patient finding metrics that flow directly into our highest-level company goals