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GSK

Applied AI Engineer

GSK

. Provide tailored guidance to business units on AI/ML use cases, feasibility, model selection, and deployment options .

Posted 9/17/2026full-timeUpper Providence • Pennsylvania • United StatesJuniorMid-Level💰 $136,125 - $226,875 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in developing and deploying machine learning models, with a strong foundation in Python and relevant frameworks. Capable of translating stakeholder requirements into technical solutions while embedding ethical considerations and fostering AI literacy within teams.

Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProgrammingCloud Platforms (GCP, AWS, Azure)Containerization (Docker, Kubernetes)Cross-Functional Team Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningDeep LearningFeature EngineeringModel EvaluationSupervised LearningUnsupervised LearningExperiment TrackingLLM-Based ApplicationsMLOps PracticesStatistical Analysis
Soft Skills
CommunicationWorkshop FacilitationStakeholder EngagementTeam CollaborationTraining and Mentoring
Tools & Technologies
PyTorchTensorFlowJAXScikit-learnPandasNumpyDockerKubernetesGit/GitHubCI/CD for ML
Industry Keywords
HealthcarePharmaBiotechBioinformaticsDrug DiscoveryGenomicsClinical DataBiological Data AnalysisResponsible AIAI Ethics

Tech Stack

Tools & technologies
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact
  • Provide tailored guidance to business units on AI/ML use cases, feasibility, model selection, and deployment options
  • Co-design prototypes and proof-of-concepts with product and domain teams
  • Translate stakeholder requirements into scoped technical solutions with success criteria and handover plans
  • Build, train, evaluate, and iterate on machine learning models for scientific and business problems
  • Package trained models into production-ready APIs and containerized deployments using GSK’s cloud infrastructure
  • Develop and maintain agentic AI systems, multi-agent architectures, and LLM-based tools
  • Share reusable patterns, baseline models, and tested pipelines for common AI/ML tasks
  • Embed privacy, ethics, and regulatory considerations into engagements
  • Run workshops, seminars, and hands-on training sessions to increase AI literacy
  • Embed within business/research units for typically 6–8 week engagements to accelerate delivery and transfer skills
  • Communicate issues, requests, and opportunities from business units to AI/ML product leads

Requirements

What you’ll need
  • Bachelor’s degree in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Statistics, Engineering, or a related quantitative discipline; OR equivalent professional experience as a software/ML engineer
  • 2+ years of professional experience developing and deploying machine learning models with a Bachelor’s; 2+ years with a Master’s or PhD
  • Expertise in Python, including PyTorch, TensorFlow, JAX, scikit-learn, pandas, and numpy
  • Experience with cloud platforms (GCP, AWS, or Azure) and containerization (Docker, Kubernetes)
  • Strong understanding of ML fundamentals: supervised/unsupervised learning, deep learning, model evaluation, feature engineering, and experiment tracking
  • Experience working in cross-functional teams and communicating technical concepts to non-technical stakeholders
  • Experience working in healthcare, pharma, or biological domains
  • Preferred: experience in pharma, biotech, or life sciences, particularly drug discovery, genomics, clinical data, or biological data analysis
  • Preferred: hands-on experience building LLM-based applications, agentic AI systems, RAG pipelines, or multi-agent architectures
  • Preferred: experience with knowledge graph construction, causal inference, or large perturbation models
  • Preferred: familiarity with single-cell RNA-seq, spatial transcriptomics, CRISPR assay data, or other high-dimensional biological datasets
  • Preferred: experience with MLOps practices, including CI/CD for ML, model monitoring, experiment tracking, and reproducible research workflows
  • Preferred: contributions to open-source ML/AI projects or peer-reviewed publications in applied ML
  • Preferred: background or demonstrated interest in responsible AI, AI ethics, or model governance
  • Preferred: strong software engineering practices including Git/GitHub, code review, testing, and documentation
  • Preferred: experience evaluating and integrating third-party AI/ML vendor tools and platforms

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
  • Comprehensive benefits program for US employees