Senior AI Platform Engineer (AI)

Location: London, United Kingdom

Company

IQVIA provides clinical research services, commercial insights, and healthcare intelligence for life sciences and healthcare organizations, building solutions that support medical treatment development and population health.

What you will do

• Design, build, and support AI platform infrastructure for large-scale machine learning and LLM initiatives.
• Translate AI research requirements into scalable infrastructure solutions and collaborate with research, data engineering, MLOps, infrastructure, and product teams.
• Develop and optimize cloud and on-premise compute environments, including GPU-enabled platforms.
• Improve the performance, reliability, scalability, automation, monitoring, and operational excellence of model training and inference workloads.
• Establish best practices for model lifecycle management, reproducibility, dataset versioning, governance, experimentation, and production deployment.
• Evaluate and implement technologies that improve AI platform capabilities, engineering standards, and developer productivity.

Requirements

• Experience building, operating, or supporting large-scale AI, machine learning, cloud, or distributed systems platforms.
• Strong understanding of cloud infrastructure, containerized environments, and modern platform engineering practices.
• Experience with machine learning workloads and the infrastructure supporting model training and deployment.
• Knowledge of AWS and infrastructure automation technologies.
• Experience with Kubernetes, Slurm, Ray, or similar orchestration and distributed compute technologies.
• Hands-on experience with Python and modern software engineering practices.
• Ability to troubleshoot performance bottlenecks and improve the efficiency of complex workloads.
• Strong communication and collaboration skills across engineering and research teams, with a passion for solving complex technical challenges and enabling innovation.

Nice to have

• Experience with large language models and generative AI platforms.
• GPU infrastructure and optimization experience.
• PyTorch and distributed training frameworks.
• LLM inference technologies such as vLLM, TensorRT-LLM, NVIDIA NIM, or similar tools.
• Model optimization techniques including quantization, LoRA, mixed-precision training, and inference optimization.
• Knowledge of knowledge graphs, large-scale data platforms, or high-performance computing environments.

Culture & Benefits

• Work on large-scale AI infrastructure challenges supporting healthcare and life sciences innovation.
• Collaborate with AI researchers, engineers, MLOps specialists, and product teams on production-ready solutions.
• Contribute to platforms that support global healthcare and life sciences organizations.
• IQVIA maintains a zero-tolerance policy for candidate fraud; application information and credentials must be truthful and complete.

Hiring process

• Submit truthful and complete application information and credentials; false statements, misrepresentations, or material omissions may result in disqualification or termination.