Machine Learning Engineer – BioSciences

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San Francisco / $80 - $95 hour

INFO

Salary
SALARY:

$80 - $95

Location

LOCATION

San Francisco

Job Type
JOB TYPE

Contract

Machine Learning Engineer - Biosciences

6 Month Contract

Hybrid in SF (3 days in, 2 remote)

We are working with a company whose mission is to defeat cancer. They are engineering programmable cell therapies aimed at overcoming cancer's complexity and improving patient outcomes.

This team is looking for an MLE to design and implement the foundational ML architecture that powers their CAR T-cell therapy discovery platforms. You will work at the intersection of advanced machine learning and immuno-oncology to optimize the development of personalized cell therapies.

Responsibilities:

  • Architect and implement the ML systems that power our CAR T-cell therapy discovery platform, optimizing performance and scalability in a clinical research environment.
  • Analyze machine learning workflows, identify bottlenecks, and implement solutions to improve efficiency.
  • Establish MLOps standards for the organization, including experiment tracking, model versioning, and building automated deployment pipelines for ML models.
  • Lead the integration of ML platforms with other software systems and tools, enabling seamless data flow across the CAR T-cell discovery pipeline.
  • Work closely with interdisciplinary teams, including product, design, front-end, machine learning, and infrastructure teams, to ensure cohesive integration of ML into the discovery process.
  • Train and mentor fellow machine learning engineers, fostering a culture of knowledge-sharing and continuous learning around CAR T-cell therapy applications.

Requirement:

  • In-depth experience with CAR T-cell therapies, including a solid understanding of their biological mechanisms and their use in cancer immunotherapy.
  • Proven expertise in architecting, building, and optimizing machine learning systems from the ground up, particularly for biological data and cell therapy applications.
  • Skilled in applying deep learning techniques to biological data, with a strong background in cell biology, immunology, or cancer research.
  • Advanced proficiency in Python, with hands-on experience using machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience designing and implementing robust data infrastructure to handle complex, high-dimensional biological datasets critical to CAR T-cell therapy discovery.

CONTACT

Amy Rzemieniewski

Senior Recruitment Consultant

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