Machine Learning Researcher - Biological Foundational Models

About Somite

Somite.ai is a venture-backed company aiming to become the OpenAI of stem cell biology, developing AI foundation models for human stem cells to drive novel cell therapies at scale.

We take a full-stack approach - generating data at 1,000x lower cost, training large-scale models with unmatched predictive power, and using these models to discover, refine, and optimize high-impact applications in cell therapy.

Our founding team includes repeat AI entrepreneur Dr. Micha Break stone (
Chorus.ai
, acquired for $575M), the Head of the Fundamental AI Group at MIT (pioneered the foundational research on scaling laws
), and three Harvard Medical School professors and National Academy of Sciences/Medicine members, including the Chair of the Genetics Department ed in Boston and launching operations in January 2024, Somite has raised close to $60M to date (
Forbes
).

Somite’s Core Values:

• We show up – fully accountable, all-in, doing whatever it takes

• We act with urgency – swift, decisive, proactive

• We support one another – collaborative, helpful, empathetic

Location:

Boston, MA (onsite, full-time)

About the Role:

As a Senior Machine Learning Researcher - Biological Foundational Models, you will play a key role in developing foundational models for single-cell RNA sequencing data. Working closely with other machine learning researchers and computational biologists, you’ll design cutting-edge AI solutions, contribute to pioneering research, and help build the core infrastructure driving Somite’s cell-replacement therapy platform. This role is ideal for a machine learning expert driven by scientific inquiry and eager to pioneer biological discoveries through foundational AI models.

Responsibilities:

• Design, train, and optimize foundational models for single-cell RNA sequencing and other high-dimensional omics data

• Collaborate closely with computational biologists to ensure models produce biologically meaningful, interpretable outputs, engaging deeply with biological questions and research

• Design and implement novel deep learning architectures, including transformer-based models tailored to biological data

• Build scalable, distributed pipelines for training and inference across trillion-token biological datasets

• Provide mentorship and technical guidance to other machine learning researchers on the team

Qualifications:

• 6+ years of experience in machine learning, transformer-based deep learning, and large-scale data analysis, preferably in biological applications

• Master’s degree or higher in Computer Science, Artificial Intelligence, Computational Biology, or a related field

• Strong proficiency in Python and deep learning frameworks such as Py Torch or Tensor Flow

• Proven experience building and optimizing large-scale models, including transformer-based architectures

• Demonstrated track record of independent research and end-to-end model development, from prototyping to production

• Passion for AI-driven biology and its potential to transform healthcare

Preferred Qualifications:

• Strongly preferred: PhD with a strong publication record in top machine learning and/or computational biology journals

• Strongly preferred: extensive background in biological research and biological modeling, ideally with single-cell RNA sequencing data

• Experience with reinforcement learning (e.g., RLHF, PPO), diffusion models, or multi-modal architectures applied to structured, high-dimensional data

• Experience in startups or fast-paced environments, with a self-directed, proactive work style

Benefits:

• Take a technical leadership role with a mission-driven company with the potential to significantly impact the lives of millions

• Work alongside a talented and passionate team at the forefront of AI and cellular biology

• Contribute to the development of groundbreaking therapies that address significant unmet medical needs

• Enjoy a competitive salary and benefits package, including flexible work options

Exceptional candidates who demonstrate outstanding capabilities and potential will be considered, even if they do not meet every qualification listed.

Join us and help unlock the full potential of AI for the benefit of human health!