Lead and support benchmarking of GPU platforms for machine learning and AI workloads, evaluating performance and optimizing hardware and software stacks.
Locations (3)
Amsterdam, North Holland, Netherlands
Europe
United States
Responsibilities
Work closely with hardware and development teams to profile and analyse GPU performance at the system and kernel level.
Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g., CUDA, ROCm).
Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks.
Perform acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability.
Requirements
Nice to have: LLM inference frameworks (vLLM, SGLang, TensorRT)
Nice to have: performance profiling tools (Nsight, nvprof, perf)
Nice to have: cloud ML platforms (AWS, GCP, Azure ML)
Lead software development projects and provide technical leadership to a team of software engineers, focusing on IBM WebSphere and middleware modernization.
Responsibilities
Design, create, test and document software systems and applications in accordance with agreed development and security standards
Lead software development projects and provide technical leadership to their teams
Manage software planning, development, and construction activities
Evaluate and resolve complex issues within the development and production environments
Collaborate with business analysts, testers, and other developers to deliver high-quality software on secure platforms
Senior Software Engineer responsible for designing, building, and evolving cloud‑native platforms using AWS serverless technologies and MongoDB.
Responsibilities
Owning the design and delivery of high‑quality software solutions, working end‑to‑end across features, services, and systems to deliver meaningful customer and business outcomes
Building and operating cloud‑native, serverless applications on AWS, ensuring solutions are secure, resilient, scalable, and optimised for performance and cost
Leading by example in applying clean code, sound architectural principles, and engineering best practices that align with Legal & General’s SSDLC and technology strategy
Actively identifying, prioritising, and addressing technical debt, ensuring long‑term maintainability, reliability, and operability of our platforms
Defining and influencing test strategies that raise the quality bar, with a strong focus on security, accessibility, usability, resilience, and non‑functional requirements
Senior MLOps & Cloud Infrastructure Engineer responsible for building, operating, and evolving the cloud infrastructure and engineering platforms behind production AI systems.
Responsibilities
Design, provision, and operate scalable infrastructure on GCP
Manage containerised applications and ML workloads with Kubernetes
Build reproducible infrastructure using Terraform
Design and improve CI/CD pipelines for backend services and data pipelines
Improve service availability, resilience, and incident response
Senior Azure Data Platform Engineer / Architect to support a major enterprise data platform uplift for a leading Australian financial services organisation.
Responsibilities
Assess and uplift existing Azure data platform components.
Analyse and document dependencies across ingestion pipelines, business rules and semantic models.
Migrate and optimise ETL/ELT processes.
Develop and implement Azure data engineering solutions.
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