Senior AI Research Scientist, Explainable Artificial Intelligence
Imago BioSciences
Job Description
Our Artificial Intelligence Machine Learning (AI/ML) capabilities are critical accelerators to our mission of inventing 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 and elucidating complex disease mechanisms. As a senior AI scientist, you will be responsible for extracting biological insights from foundation models, developing new methods for post-hoc and intrinsic explainability of AI models, building rigorous benchmarks, evaluations, as well as fit-for-purpose datasets for answering specific biological questions. Your work will advance our understanding of complex diseases and support the development of innovative therapeutic strategies. You will be part of a cross-functional team of computational biologists, data scientists, software engineers, and machine learning researchers.
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, Computational Biology, or related STEM field and 0-3+ years of full-time experience (with PhD), 4+ years of experience (with MS), or 7+ years of experience (with BS).
Demonstrated experience in using biological foundation models for solving classical bioinformatics tasks, extracting new biological insights, and critically assessing model outputs.
Demonstrated expertise in classical machine learning as well as modern deep learning approaches with a particular emphasis on graph neural networks.
Experience in fine-tuning, evaluating, and debugging modern AI models and data at scale.
Excellent software design and development skills and strong proficiency in Python.
Experience with standard deep learning frameworks like the PyTorch ecosystem for working with large foundation models.
Excellent communication skills and ability to work collaboratively in a multi-disciplinary team.
Preferred Skills and Experience
Experience working with models that require multiple GPUs for inference.
Relevant publications in scientific journals and experience contributing to research communities, including NeurIPS, ICML, ICLR, etc
Experience with multi-modal (biological or otherwise) foundation models is a strong plus.
#EligibleforERP
Required Skills:
Artificial Intelligence (AI), Data Engineering, Data Science, Deep Learning, Foundation Model Fine Tuning, Foundation Models, Genomics, Machine Learning (ML), Python (Programming Language), PyTorch, Software Development, Transformer ModelPreferred Skills:
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Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.
The salary range for this role is
$144,800.00 - $227,900.00This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.
The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.
We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.
You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.
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RegularRelocation:
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04/17/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.