Coders Connect
Senior Machine Learning Scientist (Multimodal Drug Discovery)
Coders Connect, South San Francisco, California, us, 94083
Senior Machine Learning Scientist
Coders Connect is collaborating with a cutting-edge biotech startup redefining how foundational biology meets AI. Their mission? Train multimodal foundation models from real human biological data to revolutionize drug discovery. What You'll Be Doing: We're seeking a Senior Machine Learning Scientist with a deep interest in applying state-of-the-art ML techniqueslike transformers and diffusion modelsto problems at the frontier of computational biology. Design and develop multimodal foundation models for gene regulation and drug response Integrate chemical structure, protein sequences, and single-cell transcriptomics into unified models Adopt and implement latest advances in deep learning (e.g., self-supervised learning, FSDP, dMoE) Work in cross-functional teams with biologists, engineers, and data scientists Drive hypothesis generation using ML and contribute to novel biological insights Requirements: PhD or equivalent practical experience in a technical/ML-focused field Proven experience with deep learning (transformers, GNNs, SSMs, diffusion models, etc.) Strong skills in PyTorch, JAX, or TensorFlow, and scientific libraries like NumPy, Pandas Motivation to apply ML to real-world biological or chemical datasets Bias toward rapid prototyping and practical outcomes Bonus Points For: Prior work in computational biology or drug discovery Experience with contrastive/multimodal/self-supervised learning Familiarity with large-scale distributed training and GPU optimizations The Stack: Python, PyTorch/JAX/TensorFlow Large-scale ML toolkits (e.g., flash attention, FSDP) Transcriptomics, protein sequence data, chemical structure modeling Benefits: Unlimited PTO Monthly lunch allowance + remote office setup stipend Premium medical, dental, and vision coverage for employees and dependents Hybrid flexibility from South San Francisco or Toronto
Coders Connect is collaborating with a cutting-edge biotech startup redefining how foundational biology meets AI. Their mission? Train multimodal foundation models from real human biological data to revolutionize drug discovery. What You'll Be Doing: We're seeking a Senior Machine Learning Scientist with a deep interest in applying state-of-the-art ML techniqueslike transformers and diffusion modelsto problems at the frontier of computational biology. Design and develop multimodal foundation models for gene regulation and drug response Integrate chemical structure, protein sequences, and single-cell transcriptomics into unified models Adopt and implement latest advances in deep learning (e.g., self-supervised learning, FSDP, dMoE) Work in cross-functional teams with biologists, engineers, and data scientists Drive hypothesis generation using ML and contribute to novel biological insights Requirements: PhD or equivalent practical experience in a technical/ML-focused field Proven experience with deep learning (transformers, GNNs, SSMs, diffusion models, etc.) Strong skills in PyTorch, JAX, or TensorFlow, and scientific libraries like NumPy, Pandas Motivation to apply ML to real-world biological or chemical datasets Bias toward rapid prototyping and practical outcomes Bonus Points For: Prior work in computational biology or drug discovery Experience with contrastive/multimodal/self-supervised learning Familiarity with large-scale distributed training and GPU optimizations The Stack: Python, PyTorch/JAX/TensorFlow Large-scale ML toolkits (e.g., flash attention, FSDP) Transcriptomics, protein sequence data, chemical structure modeling Benefits: Unlimited PTO Monthly lunch allowance + remote office setup stipend Premium medical, dental, and vision coverage for employees and dependents Hybrid flexibility from South San Francisco or Toronto