Somite AI
Senior / Principal Machine Learning Engineer - Biological Foundational Models
Somite AI, Boston, Massachusetts, us, 02298
Overview
Senior / Principal Machine Learning Engineer - Biological Foundational Models at Somite AI. Somite.ai is a venture-backed company transforming stem cell biology with AI. We are decoding the language of cells to enable therapy development, with our DeltaStem platform accelerating therapy creation through data-driven insights. Founded by Dr. Micha Breakstone and Harvard Medical School professors, Somite.ai is at the forefront of AI-enabled biology and healthcare innovation. About the Role
As a Machine Learning Engineer - Biological Foundational Models, you will help develop foundational models for single-cell RNA sequencing data. You will collaborate with machine learning researchers and computational biologists to design cutting-edge AI solutions, contribute to research, and help build the core infrastructure for Somite’s cell-replacement therapy platform. Responsibilities
Drive the development of machine learning models for biological data from research and prototyping to production deployment. Design, train, and optimize foundational models for single-cell RNA sequencing and other high-dimensional omics data. Build scalable, distributed pipelines for training and inference across large-scale biological datasets. Collaborate with computational biologists to ensure models produce biologically meaningful, interpretable outputs. Design and implement novel deep learning architectures, including transformer-based models tailored to biological data. Qualifications
7+ years of experience in machine learning, 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 PyTorch or TensorFlow. 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
Extensive background in biological research and biological modeling, ideally with single-cell RNA sequencing data. 3+ years of professional software engineering experience in an industry setting. Experience with reinforcement learning techniques such as RLHF, PPO. Experience in startups or fast-paced environments with a self-directed, proactive work style. What We Offer
Technical leadership role with a mission-driven company impacting lives. Collaborative team at the forefront of AI and cellular biology. Opportunities to contribute to groundbreaking therapies addressing unmet medical needs. Competitive salary and benefits, including flexible work options. Exceptional candidates who demonstrate outstanding capabilities and potential will be considered, even if they do not meet every qualification listed. Inferred from the description
Medical insurance Vision insurance 401(k) Paid maternity leave Paid paternity leave Disability insurance
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Senior / Principal Machine Learning Engineer - Biological Foundational Models at Somite AI. Somite.ai is a venture-backed company transforming stem cell biology with AI. We are decoding the language of cells to enable therapy development, with our DeltaStem platform accelerating therapy creation through data-driven insights. Founded by Dr. Micha Breakstone and Harvard Medical School professors, Somite.ai is at the forefront of AI-enabled biology and healthcare innovation. About the Role
As a Machine Learning Engineer - Biological Foundational Models, you will help develop foundational models for single-cell RNA sequencing data. You will collaborate with machine learning researchers and computational biologists to design cutting-edge AI solutions, contribute to research, and help build the core infrastructure for Somite’s cell-replacement therapy platform. Responsibilities
Drive the development of machine learning models for biological data from research and prototyping to production deployment. Design, train, and optimize foundational models for single-cell RNA sequencing and other high-dimensional omics data. Build scalable, distributed pipelines for training and inference across large-scale biological datasets. Collaborate with computational biologists to ensure models produce biologically meaningful, interpretable outputs. Design and implement novel deep learning architectures, including transformer-based models tailored to biological data. Qualifications
7+ years of experience in machine learning, 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 PyTorch or TensorFlow. 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
Extensive background in biological research and biological modeling, ideally with single-cell RNA sequencing data. 3+ years of professional software engineering experience in an industry setting. Experience with reinforcement learning techniques such as RLHF, PPO. Experience in startups or fast-paced environments with a self-directed, proactive work style. What We Offer
Technical leadership role with a mission-driven company impacting lives. Collaborative team at the forefront of AI and cellular biology. Opportunities to contribute to groundbreaking therapies addressing unmet medical needs. Competitive salary and benefits, including flexible work options. Exceptional candidates who demonstrate outstanding capabilities and potential will be considered, even if they do not meet every qualification listed. Inferred from the description
Medical insurance Vision insurance 401(k) Paid maternity leave Paid paternity leave Disability insurance
#J-18808-Ljbffr