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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Scientist - **Company:** CareerCircle - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $144,800.0 - $227,900.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Bioinformatics, Computational Biology, Directed Acyclic Graph (Directed Graphs), Python (Programming Language), Machine Learning, Software Engineering, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Information Technology, GPT, Programming Languages - **Published:** September 16, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/ma/cambridge/d775fff1-0e57-4c52-a29e-b993da4f2887 ## About the Role * PhD in Computer Science, Applied Math, Physics, Computational Biology, Biostatistics, Bioinformatics, Engineering, AI/ML, Genetics/Genomics, or a related STEM field. * Strong expertise and experience in modern AI/ML approaches, training and working with large transformer-based Foundation models, representation learning, diffusion models, and related methodologies. * Experience with pre-training large-scale and/or multi-modal Foundation Models on multiple GPUs. * Proficiency in programming languages such as Python, and experience with standard deep learning frameworks like the PyTorch ecosystem. * Interest in life sciences problems and disease biology, and willing to learn from and teach others. * Excellent communication skills and ability to work collaboratively in multi-disciplinary team. Preferred Skills and Experience * Familiarity and prior experience with biological data and biological foundation models are strong pluses. * Relevant publications in scientific journals and experience contributing to research communities, including NeurIPS, ICML, ICLR, etc. #EligibleforERP, Algorithms, Applied Mathematics, Artificial Intelligence (AI), Biological Data Analysis, Computational Sciences, Data Science, Deep Learning, Foundation Models, Genomics, Machine Learning (ML), Machine Learning Algorithms, Programming Languages, Python (Programming Language), PyTorch, Representation Learning, Transformer Model ## Description Physics Research Genetics Genomics Innovation Algorithms Biomarkers Compassion Data Science Communication Data Analysis Life Sciences Biostatistics Deep Learning Bioinformatics Disease Biology Computer Science Machine Learning Telephone Skills Feature Learning Applied Mathematics Software Engineering Contingent Workforce Willingness To Learn Programming Languages Computational Biology Artificial Intelligence Machine Learning Algorithms Python (Programming Language) PyTorch (Machine Learning Library) Transformer (Machine Learning Model) Directed Acyclic Graph (Directed Graphs), Our Artificial Intelligence and Machine Learning (AI/ML) capabilities are critical accelerators of our mission to invent new medicines that save and improve lives. Core to the Data, AI, and Genome Sciences (DAGS) function is an AI/ML-first approach to improving target and biomarker discovery, validation, and selection, and elucidating complex disease mechanisms. As Senior Machine Learning Scientist, you will be responsible for developing and training large scale Foundation Models based on biological data. Your work will advance our understanding of complex diseases and support the development of innovative therapeutic strategies. In this pursuit, you will have at your disposal high-performance clusters with several hundred state-of-the-art GPUs, access to biological, computational, and engineering experts from across Our Company and external vendors. You will be part of a broader, cross-functional team of computational biologists, data scientists, software engineers, and machine learning researchers who strive to identify therapeutic targets and biomarkers. Primary Responsibilities * Collaborate with cross-functional team to identify research questions, data requirements, and develop appropriate, modern AI/ML solutions. * Design and develop, train, and implement novel ML algorithms particularly transformer-based Foundation Models for Target and Biomarker discovery leveraging large scale biological data. * Stay up to date with the latest advancements in modern AI/ML approaches and apply relevant advancements to improve existing methodologies and models. * Publish research findings in relevant conferences and journals, and actively contribute to the scientific community through knowledge sharing and collaborations., Physics Research Genetics Genomics Innovation Algorithms Biomarkers Compassion Data Science Communication Data Analysis Life Sciences Biostatistics Deep Learning Bioinformatics Disease Biology Computer Science Machine Learning Telephone Skills Feature Learning Applied Mathematics Software Engineering Contingent Workforce Willingness To Learn Programming Languages Computational Biology Artificial Intelligence Machine Learning Algorithms Python (Programming Language) PyTorch (Machine Learning Library) Transformer (Machine Learning Model) Directed Acyclic Graph (Directed Graphs) +0 Google IT Automation with Python Senior Machine Learning Scientist, Foundation Model Merck & Co., Inc Cambridge, MA*On-Site Biology Physics Research Genetics Genomics Innovation Algorithms Biomarkers Compassion Data Science Communication Data Analysis Life Sciences Biostatistics Deep Learning Bioinformatics Disease Biology Computer Science Machine Learning Telephone Skills Feature Learning Applied Mathematics Software Engineering Contingent Workforce Willingness To Learn Programming Languages Computational Biology Artificial Intelligence Machine Learning Algorithms Python (Programming Language) PyTorch (Machine Learning Library) Transformer (Machine Learning Model) Directed Acyclic Graph (Directed Graphs) +0 ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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