Machine Learning Research Engineer

Overview I am working with a leading Tech Bio company in Boston, looking for 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. tailorable 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. Qualifications 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, 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, is a strong plus, given the complexity of multi-scale integration. Experience working on 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 #J-18808-Ljbffr

Created: 2025-09-17