Senior AI Platform Engineer
At a glance
Senior ML Platform & Ops role at IQVIA. London · full-time · no salary stated · we estimate £96,000–£116,772 across the United Kingdom.
IQVIA has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the AI infrastructure roadmap and turn research needs into engineering plans for LLM initiatives
- Build compute environments with infrastructure teams, covering AWS, on-premises systems, GPUs, Slurm and research workflow migration
- Improve training and inference performance, scalability and reliability for research and product teams
- Create dataset versioning, lineage, reproducibility and model registry capabilities, while advancing knowledge graph infrastructure
- Coordinate delivery across research, data, MLOps, product and infrastructure teams; guide vendors, standards and engineer development
What you bring
- Substantial experience operating enterprise-scale AI, machine learning or distributed computing platforms
- Strong command of LLM design, GPU infrastructure, distributed training, and high-performance inference methods
- Hands-on expertise tuning and profiling GPU workloads, including model optimization techniques and related tools
- A strong foundation in AWS, HPC, distributed systems, containers, automation and workload orchestration
- A record of leading complex cross-team work and connecting research systems with secure, reliable production operations
Who this fits
This senior technical leadership role suits someone who can set platform direction while staying close to infrastructure and performance engineering. You’ll work across research, product, data, MLOps and infrastructure teams, and mentor engineers. The role is based in London, United Kingdom.
From the employer
Senior AI Platform Engineer
The Senior AI Platform Engineer is responsible for defining and delivering the infrastructure strategy underpinning IQVIA's Large Language Model (LLM) programmes. This role provides technical leadership across compute, data, model lifecycle management, evaluation frameworks, and platform engineering, ensuring research innovations can be successfully transformed into secure, scalable, and production-ready AI solutions.
Acting as a key technical leader and cross-functional integrator, the Senior AI Platform Engineer partners with research, product, infrastructure, data engineering, and MLOps teams to design and operate the platforms required to train, evaluate, deploy, and govern large-scale AI systems across IQVIA products and healthcare use cases.
Key Responsibilities
- Own the AI platform and infrastructure roadmap, leading the planning and execution of LLM initiatives and translating research requirements into scalable engineering solutions.
- Partner with centralised infrastructure teams to design and deliver high-performance compute environments across AWS and on-premises platforms, including GPU infrastructure, Slurm clusters, and migration from ad hoc research workflows.
- Optimise LLM training and inference workloads, supporting research and product teams in maximising performance, scalability, and reliability across the infrastructure stack.
- Establish and maintain model and data lifecycle capabilities, including dataset versioning, lineage tracking, reproducibility standards, and integration with model registries.
- Lead the evolution of knowledge graph infrastructure, driving technology selection, migration strategies, performance optimisation, and integration with AI workflows.
- Serve as the primary technical coordination point across AI Research, Data Engineering, MLOps, Product, and Infrastructure teams, resolving dependencies and prioritising activities critical to delivery.
- Provide technical leadership for vendor selection, procurement, and technology partnerships, advising on compute architectures, GPU specifications, AI platforms, and integration approaches.
- Define platform engineering standards, governance, and best practices while mentoring engineers and promoting operational excellence across AI and platform teams.
Skills & Experience
- Significant experience designing, building, and operating large-scale AI, machine learning, or distributed computing platforms in enterprise environments.
- Deep understanding of LLM architectures and their interaction with GPU infrastructure, including CUDA, cuDNN, NCCL, kernel-level acceleration libraries, and distributed training frameworks such as PyTorch.
- Strong knowledge of distributed training and inference strategies, including tensor, pipeline, data, and expert parallelism approaches.
- Experience optimising LLM inference workloads using technologies such as vLLM, TensorRT-LLM, NVIDIA NIM, SGLang, or similar high-performance serving frameworks.
- Expertise in model optimisation techniques including quantisation, mixed precision training and inference (FP8, GPTQ, AWQ, LoRA), and performance tuning for large-scale model deployment.
- Advanced experience profiling, troubleshooting, and optimising GPU workloads using tools such as NVIDIA Nsight, DCGM, and related ecosystem technologies.
- Strong background in AWS cloud services, high-performance computing, distributed systems, containerised environments, and infrastructure automation.
- Experience with workload orchestration technologies such as Slurm, Kubernetes, Ray, or equivalent distributed compute frameworks.
- Demonstrated success bridging research and production environments, enabling rapid experimentation while maintaining operational excellence, governance, security, and reliability.
- Proven ability to lead complex cross-functional initiatives, influence technical direction, and communicate effectively with engineering, research, product, and executive stakeholders.
Why Join?
Those who join us become part of a recognized global leader still willing to challenge the status quo to improve patient care. You will have access to the most cutting-edge technology, the largest data sets, the best analytics tools and, in our opinion, some of the finest minds in the Healthcare industry.
You can drive your career at IQVIA and choose the path that best defines your development and success. With exposure across diverse geographies, capabilities, and vast therapeutic and information and technology areas, you can seek opportunities to change and grow without boundaries.
Regardless of your role, we invite you to reimagine healthcare with us. You will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately improve human health outcomes.
It's an exciting time to join and reimagine what's possible in healthcare.
IQVIA is a strong advocate of diversity and inclusion in the workplace. We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success. We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximize their personal potential.
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.