Umbilical Life
Machine Learning Research Engineer (Senior/Principal/Staff)
Umbilical Life, Boston, Massachusetts, us, 02298
Overview
I am working with a leading Tech Bio company in Boston, seeking a Senior (Senior/Principal/Staff Scientist) Machine Learning Research Engineer to lead the development of their Biological AI Model. The candidate should be local to Boston on a weekly basis. Key Responsibilities
Design and implement core
AI/ML models
for simulating cellular systems using multi-omics and single-cell data. Develop novel architectures e.g.
Graph Neural Networks, Causal Inference, Transformers, diffusion models, VAE
etc tailored to biological complexity. Contribute to the
strategic direction of modeling efforts , helping define what to build, why, and how. Lead model design from
prototyping to production . Guide internal thinking around
biological networks, perturbation models , and high-dimensional cellular data. Support cross-functional collaboration and help define a scalable modeling stack and modeling best practices across the company. Ideal Profile
MS or PhD in Computer Science, Physics, Applied Math, or similar , with a strong focus on AI/ML. Strong track record in research outputs on single-cell data and AI method development. Expertise in building models using
GNNs, VAEs, Transformers ,
reinforcement learning , or other deep learning approaches. Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow or JAX. Exposure to
single-cell data (e.g., scRNA-seq, spatial omics) . Ability to abstract and model
complex biological processes
from data/physics/ML perspectives. Experience with
scaling models across biological levels
from individual cells to tissues and whole organisms and
multi-scale integration
is a strong plus. Experience working on
noisy, high-dimensional, multi-modal biological data . Curious, collaborative, and comfortable in fast-moving, exploratory R&D environments. Previous experience with Virtual Cell Models is a plus. Seniority level
Mid-Senior level Employment type
Full-time Job function
Science and Engineering Industries
Biotechnology Research and Pharmaceutical Manufacturing
#J-18808-Ljbffr
I am working with a leading Tech Bio company in Boston, seeking a Senior (Senior/Principal/Staff Scientist) Machine Learning Research Engineer to lead the development of their Biological AI Model. The candidate should be local to Boston on a weekly basis. Key Responsibilities
Design and implement core
AI/ML models
for simulating cellular systems using multi-omics and single-cell data. Develop novel architectures e.g.
Graph Neural Networks, Causal Inference, Transformers, diffusion models, VAE
etc tailored to biological complexity. Contribute to the
strategic direction of modeling efforts , helping define what to build, why, and how. Lead model design from
prototyping to production . Guide internal thinking around
biological networks, perturbation models , and high-dimensional cellular data. Support cross-functional collaboration and help define a scalable modeling stack and modeling best practices across the company. Ideal Profile
MS or PhD in Computer Science, Physics, Applied Math, or similar , with a strong focus on AI/ML. Strong track record in research outputs on single-cell data and AI method development. Expertise in building models using
GNNs, VAEs, Transformers ,
reinforcement learning , or other deep learning approaches. Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow or JAX. Exposure to
single-cell data (e.g., scRNA-seq, spatial omics) . Ability to abstract and model
complex biological processes
from data/physics/ML perspectives. Experience with
scaling models across biological levels
from individual cells to tissues and whole organisms and
multi-scale integration
is a strong plus. Experience working on
noisy, high-dimensional, multi-modal biological data . Curious, collaborative, and comfortable in fast-moving, exploratory R&D environments. Previous experience with Virtual Cell Models is a plus. Seniority level
Mid-Senior level Employment type
Full-time Job function
Science and Engineering Industries
Biotechnology Research and Pharmaceutical Manufacturing
#J-18808-Ljbffr