Umbilical Life
Machine Learning Research Engineer (Bio)
Umbilical Life, Boston, Massachusetts, United States, 02298
Machine Learning Research Engineer (Bio)
Senior/Principal/Staff Scientist position in Boston to lead the development of a Biological AI Model. Local presence in Boston on a weekly basis is required. Key Responsibilities
Design and implement core
AI/ML models
for simulating cellular systems using multi-omics and single-cell data. Develop novel architectures such as
Graph Neural Networks, Causal Inference, Transformers, diffusion models, VAEs
, 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/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)
. Strong ability to abstract and model
complex biological processes
from a data/physics/ML perspective. Experience with
scaling models across biological levels
from individual cells to tissues and whole organisms; multi-scale integration is a strong plus. Experience working with
noisy, high-dimensional, multi-modal biological data sets
. 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 Pharmaceutical Manufacturing
#J-18808-Ljbffr
Senior/Principal/Staff Scientist position in Boston to lead the development of a Biological AI Model. Local presence in Boston on a weekly basis is required. Key Responsibilities
Design and implement core
AI/ML models
for simulating cellular systems using multi-omics and single-cell data. Develop novel architectures such as
Graph Neural Networks, Causal Inference, Transformers, diffusion models, VAEs
, 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/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)
. Strong ability to abstract and model
complex biological processes
from a data/physics/ML perspective. Experience with
scaling models across biological levels
from individual cells to tissues and whole organisms; multi-scale integration is a strong plus. Experience working with
noisy, high-dimensional, multi-modal biological data sets
. 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 Pharmaceutical Manufacturing
#J-18808-Ljbffr