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GSK

Senior Forward Deployed Engineer – Physical AI, Self-Driving Labs

GSK

. Own high-priority business-unit use cases from problem framing through working prototypes at a days-to-weeks cadence .

Posted 10/27/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong full-stack and AI/ML engineering capabilities, with proficiency in Python and TypeScript/JavaScript. Experienced in lab automation, self-driving lab workflows, and utilizing NVIDIA Omniverse for simulation and tech transfer.

Highest-signal resume keywords
Full-Stack EngineeringAI/ML EngineeringPython ProficiencyLab Automation ExperienceNVIDIA Omniverse Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Production DeploymentsGenAI PatternsMulti-Agent OrchestrationPrompt EngineeringPredictive ModelingAnomaly Detection ModelingRobotics IntegrationDigital-to-Physical OrchestrationComputer VisionEmbedded Systems
Soft Skills
CoachingMentoringCollaboration
Tools & Technologies
NVIDIA OmniverseClaude CodeGitHub CopilotDatabricks AI AssistantNemotron
Industry Keywords
Regulated IndustriesGxPGDPRSOXManufacturing Execution SystemsLab Execution Systems

Tech Stack

Tools & technologies
JavaScriptPythonTypeScriptGo

About the role

Key responsibilities & impact
  • Own high-priority business-unit use cases from problem framing through working prototypes at a days-to-weeks cadence
  • Form defensible recommendations on whether use cases should continue or be discontinued
  • Ship initial production versions where the path is clear before handoff to the Senior Solutions Engineer
  • Operate AI-agent workflows for planning, coding, testing, review, and documentation
  • Embed with business-unit teams, attend standups, understand domains, and prototype using real data and workflows
  • Package proven use cases for scale-up, including working code, architecture rationale, risks, and scaling concerns
  • Build Physical AI capabilities for self-driving labs and simulated technology transfers
  • Orchestrate physical laboratory spaces from digital systems using virtual commissioning and NVIDIA Omniverse representations
  • Collaborate with automation, business, and technology teams across R&D and manufacturing
  • Initiate responsible AI, Code Orange, and Accountability Report conversations during prototyping
  • Contribute reusable agents, prompt templates, and reference architectures to the organisation’s pattern library
  • Coach business-unit engineers on AI-augmented ways of working and mentor engineers

Requirements

What you’ll need
  • Strong full-stack or AI/ML engineering experience, including production deployments
  • Strong proficiency in Python and at least one of TypeScript/JavaScript, Go, or similar
  • Hands-on experience with GenAI patterns, including agents, multi-agent orchestration, RAG, prompt engineering, and evaluation
  • Strong experience with labs, manufacturing control, edge model deployment, predictive and anomaly detection modeling, and closed-loop control
  • Strong experience in lab automation and self-driving lab workflows, including robotics, instrument integration, and digital-to-physical orchestration
  • Strong experience with physics-based or 3D simulation platforms such as NVIDIA Omniverse and Isaac Sim, applied to tech transfer
  • Experience with the NVIDIA physical AI and agentic model stack, including Nemotron
  • Daily use of AI coding agents such as Claude Code, GitHub Copilot, or Databricks AI Assistant
  • Experience as a Forward Deployed Engineer at an AI-native company or as a Customer Engineer / Solutions Architect at a hyperscaler
  • Experience in regulated industries and familiarity with GxP, GDPR, and SOX
  • Experience with Manufacturing Execution Systems or Lab Execution Systems
  • Experience extending lab automation into quality labs and manufacturing lines
  • Strong experience in computer vision, embedded systems, and edge AI
  • Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience

Benefits

Comp & perks
  • Access to learning and development to grow technical and leadership skills
  • Supportive team environment
  • Agile working culture and flexibility opportunities
  • Adjustments and support during the recruitment process