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AI/ML Engineer – Controllable Biology
GSK. Apply machine learning and AI methods to biological networks and sequence data from large-scale human genetic, functional genomic, and single-cell experiments .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in applying machine learning and AI methods to biological networks and sequence data, with proficiency in Python and PyTorch for developing AI/ML-driven solutions. Strong background in systems biology and experience with biological datasets enhance capabilities in drug discovery.
Highest-signal resume keywords
Machine LearningAI MethodsPython ProgrammingPyTorch FrameworkBiological Data Analysis
ATS Keywords
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Hard Skills
Machine LearningDeep Learning AlgorithmsModel DesignModel ImplementationBiological Sequence Data AnalysisGenomicsTranscriptomicsProteomicsGene Regulatory NetworksSoftware Engineering
Soft Skills
CollaborationAccountabilityOwnership
Certifications & Qualifications
Master's DegreePhD (Preferred)
Industry Keywords
Systems BiologyDisease BiologyMolecular BiologyBiochemistryOpen-Source ContributionsPeer-Reviewed Publications
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Apply machine learning and AI methods to biological networks and sequence data from large-scale human genetic, functional genomic, and single-cell experiments
- Develop products and solutions using cutting-edge machine learning and AI
- Execute and deliver full AI/ML-driven solutions from sourcing training data through model design, implementation, testing, and benchmarking
- Design and implement state-of-the-art machine learning models
- Collaborate within the AI/ML Controllable Biology Team
- Contribute to the development of models that control biological networks for drug discovery
- Participate in continuous development and uphold ownership, accountability, and collaboration principles
Requirements
What you’ll need- Master’s degree in a related field, such as computer science, mathematics, or natural sciences
- Knowledge of machine learning, software engineering, and agentic development best practices
- Proficiency with standard deep learning algorithms and model architectures
- Experience with Python and PyTorch, or equivalent languages and machine learning frameworks
- Experience working with biological sequence and network data, including genomics, transcriptomics, proteomics, gene regulatory networks, or related biological datasets
- Advanced degree (Master's or PhD) in a quantitative or computational field is a plus
- Knowledge of systems biology, disease biology, molecular biology, and biochemistry is a plus
- Peer-reviewed publications in major AI conferences are a plus
- Track record of contributing to open-source projects is a plus
Benefits
Comp & perks- 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
- Career and development support
- Flexible/agile working culture
- Application-process adjustments where needed