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    Machine Learning Engineer - San Francisco, CA, United States - Probably Genetic

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    Description

    About Probably Genetic:

    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 Role:

    We are looking for a Machine Learning Engineer who will be pivotal as we stand up a brand new Machine Learning function and team. This role will report to our Machine Learning Lead and will be based in San Francisco.

    What You Will Do:

    You will be an early member of the team tasked with building models to accelerate the ability to achieve our mission – diagnosing 200 million patients. The team's initial objectives are 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 Machine Learning Lead and our CTO
    • Design and orchestrate machine learning experiments to improve the accuracy of our patient identification models
    • 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 4 years of experience in machine learning
    • 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 $137,000 - $202,000 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
    • 30 days of vacation a year
    • 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.

    #J-18808-Ljbffr


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