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    Machine Learning Engineer - San Francisco, United States - Genentech

    Genentech
    Genentech San Francisco, United States

    1 week ago

    Default job background
    Description
    The Position

    The Position
    A healthier future. It's what drives us to innovate.

    To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come.

    Creating a world where we all have more time with the people we love. That's what makes us Roche.
    At Genentech Computational Sciences (gCS) Prescient Design, we are revolutionizing drug discovery with cutting-edge machine learning techniques.

    We are seeking talented engineers with a passion for building large-scale, distributed machine learning algorithms and systems that will transform the drug discovery process.

    gCS Prescient Design is seeking an exceptional Machine Learning Engineer to develop our LLMs and AI product and enable the next generation of foundational research in machine learning for scientific discovery.

    We are looking for someone who is not only passionate about technical problem-solving but also has a proven track record of delivering innovative solutions in machine learning.

    The Opportunity

    As an integral part of the team, you will be involved in the end-to-end development of LLMs: data preparation and cleaning, implementation of scalable data loaders for text and multimodal data, LLM architecture design and modification for optimal performance, throughput, and inference speed, development of LLM-based products including finetuning and RAG, and development/maintenance of APIs for the users of the LLMs.

    You will participate in cutting-edge research in LLMs and methods development for drug discovery.

    You will develop LLMs including pretraining and finetuning, as well as deploy models in production environments, working closely with other engineers to ensure scalability and reliability

    You will solve core engineering challenges including the design, implementation, and scaling of our data, training, and deployment pipeline

    You will collaborate closely with cross-functional teams across both Prescient Design and gRED to solve complex problems in the life sciences

    Who you are
    You have an MS/BS in Computer Science, Statistics, related field, or equivalent experience and 2+ years of industry experience in machine learning

    You have demonstrated success in technical capabilities in developing and deploying machine learning models in production environments

    Strong programming skills in Python

    Extensive experience with deep learning and distributed training frameworks such as PyTorch and Deepspeed

    Preferred
    You have an extensive track record of delivering innovative solutions in machine learning Strong communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific and engineering leadership

    You have experience collaborating with external scientific partners, such as academic institutions or industry research groups


    You have a passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning.

    #gCS
    Relocation benefits are available for this posting

    The expected salary range for this position based on the primary location of New York City, New York is $144,900 to $269,100 of hiring range.

    Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
    Benefits
    Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us.

    Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.

    #J-18808-Ljbffr
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