Director, Data Science, Foundation Model AI
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Primary Responsibilities-
- Collaborate with cross-functional teams to identify research questions of high impact.-
- Align and prioritize the group's research and development work with our company business needs.•-
- Articulate the group's agenda and demonstrate delivered business value to diverse stakeholders.-
- Provide deep technical guidance. Oversee the training of large multi-modal foundation models. Work with data, including various omics, imaging, and text modalities.-
- Interpret and critically analyze results from machine learning and AI models.-
- Cultivate and champion a culture of AI excellence within DAGS and across our company
- Coach and advance the team of machine learning researchers.-
- Stay current with AI, machine learning, and statistics. Proactively propose and pilot promising research directions.-
- Publish research findings in relevant conferences and journals and actively contribute to the scientific community through knowledge sharing and collaborations.-
- Establish and nurture existing collaborations with academia and industry.-
- PhD in Computer Science, Statistics, Physics, Engineering, Mathematics, Data Science, AI/Machine Learning, Computational Biology, Bioinformatics, Computational Biology, or related STEM field and 7+ years of full-time experience or an MS and 10+ years of experience.-
- Deep technical expertise in classical machine learning, including probabilistic models and causal analysis. Demonstrated world-class expertise in at least one sub-area of machine learning or AI, as shown by publications in NeurIPS, ICML, ICLR, AISTATS, or equivalent venues, and/or open-source projects.-
- Experience leading teams of machine learning researchers and software engineers.-
- Experience training large models on multi-node, multi-GPU environments.•-
- Experience designing novel architectures for multi-modal foundation models. •-
- Experience in post-training foundation models, including familiarity with parameter-efficient fine-tuning, post-hoc interpretability, and preference optimization.•-
- Strong proficiency in Python and awareness of software engineering best practices.-
- Experience with standard deep learning frameworks like the PyTorch ecosystem.•-
- Excellent communication skills and ability to work collaboratively in a multi-disciplinary team.-
- Interest in life sciences problems and disease biology, and willing to learn from and teach others.-
- Experience training and working with large transformer-based models is strongly preferred.-
- Experience with modern generative modeling paradigms, such as diffusion modeling and flow matching.-
- Experience or interest in reinforcement learning (RL) and using RL for training reasoning models.-
- 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.-
AI Architecture, Artificial Intelligence (AI), Computer Science, Data Engineering, Data Science, Foundation Model Fine Tuning, Foundation Models, Generative AI, Genomics, Machine Learning (ML), Python (Programming Language), PyTorch, Software Development, Transformer Model Preferred Skills: Current Employees apply HERE Current Contingent Workers apply HERE US and Puerto Rico Residents Only: Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process. As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.--As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.- For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit: EEOC Know Your Rights EEOC GINA Supplement• We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively. Learn more about your rights, including under California, Colorado and other US State Acts U.S. Hybrid Work Model 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
$194,100.00 - $305,600.00 This 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 . You can apply for this role through (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting. San Francisco Residents Only: -We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance Los Angeles Residents Only: -We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance Search Firm Representatives Please Read Carefully-
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. -No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.- Employee Status:
Regular Relocation:
Domestic VISA Sponsorship:
Yes Travel Requirements:
10% Flexible Work Arrangements:
Hybrid Shift:
Not Indicated Valid Driving License:
No Hazardous Material(s):
n/a Job Posting End Date:
05/1/2026
*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. Requisition ID: R392839
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