Senior Applied AI Engineer at GSK delivering high - impact AI/ML solutions aligned with R&D priorities. Collaborating with cross - functional teams to build and deploy machine learning models for drug discovery.
About the role
- Generative AI Developer at ELITS developing AI Gateway and services with modern APIs. Collaborating with cross-functional teams on cloud-based AI solutions.
Responsibilities
- Develop, deploy, and maintain AI Gateway and related generative AI services
- Implement integrations with Cloud Management System, Portal, and other internal or external platforms using modern API protocols
- Configure, deploy, and optimize LLMs and AI pipelines for production workloads
- Collaborate with coworkers in the AI & Data team and other engineering groups to integrate AI services across the cloud platform
- Contribute to CI/CD pipelines, automation, and operational processes for AI services
- Maintain and operate AI infrastructure on Linux systems with proper monitoring and observability
- Develop services using TypeScript, Python, PHP, and Rust, with a strong willingness to learn new languages as required
- Participate in code reviews, unit testing, and documentation
- Support workflow automation and integration with tools such as n8n and related open-source projects
Requirements
- Advanced expertise in generative AI with a strong foundation in programming (Python, TypeScript, PHP, or Rust)
- Hands-on experience deploying and optimizing LLMs
- Working familiarity with Unix-based systems (Linux or macOS)
- General understanding of LLMs, memory and context management, and performance optimization
- Experience with prompt engineering and integration protocols (OpenAPI, MCP)
- Hands-on experience with API integration and no-code/low-code development approaches
- Knowledge of Linux systems, SQL, and DevOps practices
- Collaborative mindset for working in cross-functional teams
- Experience with workflow automation tools (n8n) and related open-source projects (e.g., Langfuse, PyTorch, Candle, Llama-CPP)
- Experience contributing to open-source AI/ML frameworks
- Familiarity with cloud orchestration and containerization using Kubernetes and Docker
- Knowledge of GPU deployment and optimization
- Experience with multimodal interfaces and data management
- Knowledge of monitoring, logging, and observability for AI workloads
Benefits
- Health insurance
- 401(k)
- Paid time off
- Flexible working arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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