Senior AI Research Scientist, Explainable Artificial Intelligence
Merck
6 months ago
Remote friendly (Cambridge, MA)
United States
IT
Primary Responsibilities
- Collaborate with cross-functional teams to identify research questions and data requirements and develop appropriate solutions.
- Develop methods for extracting insights from large transformer-based (and related state-space models) foundation models for -omics data.
- Establish rigorous benchmarks and evaluation tasks for assessing the performance of AI models.
- Stay up to date with the latest advancements in machine learning and statistics 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.
Required Education, Experience and Skills
- PhD, MS, or BS in Computer Science, Statistics, Physics, Engineering, Mathematics, Data Science, AI/Machine Learning, Computational Biology, Bioinformatics, or related STEM field (experience requirements: 0-3+ years with PhD; 4+ years with MS; 7+ years with BS).
- Demonstrated experience using biological foundation models for classical bioinformatics tasks, extracting biological insights, and critically assessing model outputs.
- Expertise in classical machine learning and modern deep learning, with emphasis on graph neural networks.
- Experience fine-tuning, evaluating, and debugging modern AI models and data at scale.
- Excellent software design/development skills and strong proficiency in Python.
- Experience with deep learning frameworks (PyTorch ecosystem) for large foundation models.
- Excellent communication and ability to work collaboratively in a multi-disciplinary team.
Preferred Skills and Experience
- Experience with models requiring multiple GPUs for inference.
- Relevant scientific publications and contributions to research communities (e.g., NeurIPS, ICML, ICLR).
- Experience with multi-modal (biological or otherwise) foundation models.
Required Skills
- Artificial Intelligence (AI), Data Engineering, Data Science, Deep Learning, Foundation Model Fine Tuning, Foundation Models, Genomics, Machine Learning (ML), Python, PyTorch, Software Development, Transformer Model.
Benefits (explicitly stated)
- Annual bonus and long-term incentive (if applicable).
- Medical, dental, vision, other insurance benefits; retirement benefits including 401(k); paid holidays and vacation; compassionate and sick days.
Application Instructions
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub if a current employee).
- Apply no later than the day before the job posting end date (04/17/2026).
- Collaborate with cross-functional teams to identify research questions and data requirements and develop appropriate solutions.
- Develop methods for extracting insights from large transformer-based (and related state-space models) foundation models for -omics data.
- Establish rigorous benchmarks and evaluation tasks for assessing the performance of AI models.
- Stay up to date with the latest advancements in machine learning and statistics 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.
Required Education, Experience and Skills
- PhD, MS, or BS in Computer Science, Statistics, Physics, Engineering, Mathematics, Data Science, AI/Machine Learning, Computational Biology, Bioinformatics, or related STEM field (experience requirements: 0-3+ years with PhD; 4+ years with MS; 7+ years with BS).
- Demonstrated experience using biological foundation models for classical bioinformatics tasks, extracting biological insights, and critically assessing model outputs.
- Expertise in classical machine learning and modern deep learning, with emphasis on graph neural networks.
- Experience fine-tuning, evaluating, and debugging modern AI models and data at scale.
- Excellent software design/development skills and strong proficiency in Python.
- Experience with deep learning frameworks (PyTorch ecosystem) for large foundation models.
- Excellent communication and ability to work collaboratively in a multi-disciplinary team.
Preferred Skills and Experience
- Experience with models requiring multiple GPUs for inference.
- Relevant scientific publications and contributions to research communities (e.g., NeurIPS, ICML, ICLR).
- Experience with multi-modal (biological or otherwise) foundation models.
Required Skills
- Artificial Intelligence (AI), Data Engineering, Data Science, Deep Learning, Foundation Model Fine Tuning, Foundation Models, Genomics, Machine Learning (ML), Python, PyTorch, Software Development, Transformer Model.
Benefits (explicitly stated)
- Annual bonus and long-term incentive (if applicable).
- Medical, dental, vision, other insurance benefits; retirement benefits including 401(k); paid holidays and vacation; compassionate and sick days.
Application Instructions
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub if a current employee).
- Apply no later than the day before the job posting end date (04/17/2026).