Machine Learning Lead
San Francisco
Full Time Senior-level / Expert USD 151K - 223K
Probably Genetic
Free DNA tests for thousands of variants related to rare disease. No credit cards, no appointments, and no insurance necessary. Take our quiz to see if you qualify!Probably Genetic is changing the lives of patients living with severe, complex diseases. Our data platform is used by drug developers and patient advocacy groups to develop and launch treatments for these patients. Our technology discovers undiagnosed patients online, analyzes their disease state using machine learning and at-home testing, and enables compliant communication with patients. In doing so, we help patients access diagnoses, clinical trials, and treatments as early as possible.
We are a tight-knit group of hard-working, ambitious problem solvers united by a mission greater than ourselves.
We do well by doing right by patients. Our annually recurring revenue is growing >6x year over year, we’re profitable, and our roadmap is packed with innovations in bioinformatics, machine learning, and drug development. We are building an all-star team to help us bring our vision to life, and we want you to be a part of it.
Probably Genetic has raised multiple rounds of funding from Silicon Valley’s best investors, including Threshold, Khosla, and Y Combinator, giving us the ability to pay competitive salaries, offer great benefits, and provide meaningful equity. We’re dedicated to ensuring your journey with us is unforgettable, with incredible team retreats to places like Barbados, the Alps, Mexico, Costa Rica, and Portugal, just to name a few.
About the roleWe are looking for a Machine Learning Lead who will run our machine learning (ML) function. This role reports directly to the Chief Technology Officer (CTO).
What you will do
You will be the first hire in a brand-new function and build our machine learning team from the ground up. You will hand-pick a team of four technologists that will report to you, and further expand the team as the company grows. Your team’s objective will initially 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, your scope will expand to additional machine learning challenges in healthcare, genetics, and drug development.
As part of this role you will:
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
Who you are:
We are looking for a few specific things that will help you succeed in this role:
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, with 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
Some things that are not required, but you will learn on the job:
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
As with all new hires at Probably Genetic, you will also need to be:
A good person. We work with some of the most marginalized populations on the planet and empathy is key
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
The salary range for this role is $151,000-$223,000 annually. Actual compensation offered will depend on several factors including but not limited to: work experience, education, skill level, and/or other business and organizational needs.
What we offer at Probably Genetic:An engaging and supportive team
Generous Flexible Time Off policy
Hybrid, flexible work
A “work from anywhere” policy, up to 4 weeks a year
Competitive equity grants
All-expenses paid quarterly team retreats
Benefits including medical and dental
This is a hybrid role that will require working on-site 3 days a week in San Francisco. Local candidates only. Relocation is not offered for this role.
Probably Genetic is committed to fostering a welcoming and inclusive work environment for people of all genders, sexuality, ethnicity, socioeconomic background and life experiences. We urge candidates of all backgrounds to apply. If you require specific accommodations as you interview or consider working with us, please let us know.
Tags: Bayesian Bioinformatics Computer Science Computer Vision Deep Learning Engineering Healthcare technology LLMs Machine Learning ML models Pipelines Statistics Testing
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Health care Team events
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