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About the Role
The AI/ML Controllable Biology Team applies machine learning and AI methods to biological networks and sequence data. Models that control biological networks have the potential to be transformative in drug discovery, empowering us to find new life-saving medicines. We are looking for a Staff AI/ML Engineer – Controllable Biology with a track record of developing SOTA deep learning models to solve challenging real-world scientific problems. You can convert biological and drug discovery challenges into well-defined machine learning problems and independently execute and deliver full AI/ML-driven solutions.
Responsibilities
- Convert complex biological questions into tractable mathematical problems that can be solved by modern computational methods.
- Decompose large problems into quarterly, measurable results and consistently work towards delivering these through engineering sprints.
- Serve as a technical mentor in a multidisciplinary engineering team, delegating tasks and guiding junior colleagues while fostering an inclusive, supportive team culture.
- Demo work early and often, balancing research and engineering velocity.
- Act as a standard-bearer for machine learning, software engineering, code review, and agentic development best practices.
- Define technical strategy and roadmaps for AI/ML products, balancing scientific needs, safety, and operational reliability.
- Communicate clearly and accurately to leadership and the broader organization.
- Partner with stakeholders to ensure models are explainable, safe, and relevant.
Requirements
- Master’s degree in a related field (e.g. computer science, mathematics or natural sciences).
- 7+ years’ experience with standard deep learning algorithms, model architectures, machine learning best practices, scalable training and deployment.
- 7+ years’ experience in software development, including code reviews, version control systems, CI/CD pipelines, software testing, technical documentation and Agile delivery methodologies.
- 5+ years’ experience in a technical lead or engineering manager role with direct reports, mentoring software engineers or machine learning practitioners.
- 7+ years’ experience with Python and PyTorch, or an equivalent machine learning framework.
- Experience working with biological sequence and network data, including genomics, transcriptomics, proteomics, gene regulatory networks or related biological datasets.
- Experience collaborating with stakeholders across multiple teams, functions and geographic regions.
Skills
- Artificial Intelligence (AI)
- Artificial Intelligence Ethics
- Classification Models
- Deep Learning
- Intelligent Automation (IA)
- Machine Learning (ML)
- Model Evaluation
- Model Validation
- Predictive Modeling
- Probabilistic Modeling
- Python (Programming Language)
- Test Documentation
Location
- Cambridge, MA
- Waltham, MA
- Rockville, MD
- San Francisco, CA
- Other US locations
- Germany
Work Type
- Hybrid
- On-site (2 days per week)
Experience Level
- Staff
- 7+ years
- 5+ years in a technical lead or engineering manager role
Education Level
- Master’s degree
- PhD (preferred)
Salary/Compensations
- US: $136,125 to $226,875 (Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA)
- US: $123,750 to $206,250 (other US locations)
- Germany: EUR 74,700 to EUR 124,500
Benefits
- Annual bonus
- Eligibility to participate in share-based long-term incentive program
- Health care and other insurance benefits (for employee and family)
- Retirement benefits
- Paid holidays
- Vacation
- Paid caregiver/parental and medical leave
About the Company
- GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together.
- We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive.
- We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines.
- We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
- Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
- We believe in an agile working culture for all our roles.
Equal Opportunity
- GSK is an Equal Opportunity Employer.
- All qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.