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iO Associates - US

Staff Machine Learning Researcher

iO Associates - US, Boston

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iO Associates are delighted to be partnered with this cutting-edge venture-backed Biotech at the forefront of combining AI and biology. They are seeking a skilled individual to join their team as a Staff Machine Learning Researcher. Located in Boston, our client is revolutionizing health technology with their innovative platform, aimed at engineering therapies for various diseases like diabetes, neurodegenerative diseases, and muscular dystrophies.


As a Staff Machine Learning Researcher, you will be pivotal in developing foundational models for single-cell RNA sequencing data. Collaborating with a team of experienced machine learning researchers and computational biologists, you will design advanced AI solutions to drive their therapy platform forward.

If you are a passionate machine learning expert eager to explore biological discoveries through AI models, this role is perfect for you.

Responsibilities:

  • Design, train, and optimize foundational models for single-cell RNA sequencing and other high-dimensional omics data
  • Collaborate with computational biologists to ensure models generate biologically meaningful outputs
  • Design and implement innovative deep learning architectures tailored to biological data
  • Build scalable pipelines for training and inference across vast biological data sets
  • Provide mentoring and technical guidance to fellow machine learning researchers
  • 6+ years of machine learning experience, preferably in biological applications
  • Master's degree or higher in Computer Science, Artificial Intelligence, or related field
  • Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow
  • Track record of building and optimizing large-scale models, including transformer-based architectures
  • Passion for AI-driven biology and health care transformation
  • PhD with a strong publication track record in machine learning or computational biology journals
  • Background in biological research and modeling, particularly in single-cell RNA sequencing
  • Familiarity with reinforcement learning, diffusion models, or multi-modal architectures applied to high-dimensional data
  • Experience in fast-paced environments or start up settings

Applicant must be based or commutable to Boston.

Seniority level

  • Seniority level

    Mid-Senior level

Employment type

  • Employment type

    Full-time

Job function

  • Job function

    Science

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