Staff Machine Learning Engineer

We’re teaming up with one of the leading names in AI, known for pushing the boundaries of what’s possible with large-scale generative models and next-gen cloud infrastructure. We're offering a rare opportunity to step into a Staff Machine Learning Engineer role and play a key part in shaping the platforms powering millions of users across the globe.

You'll be joining a team of exceptional researchers and engineers, all passionate about advancing the field and delivering world-class AI experiences.

Location:London, Oxford Street (Hybrid; onsite in London once a week)

Rate:£1000 – £1200 per day - Outside IR35

Start date:ASAP,12-month contract

What you'll be doing

• Leading the development of scalable, reliable systems for training and fine-tuning transformer-based models
• Optimising inference pipelines for real-time applications — aiming for low latency and high throughput
• Exploring and applying advanced fine-tuning methods like LoRA, prefix-tuning, and adapters
• Tuning performance across GPUs and systems using tools like DeepSpeed, Triton, TensorRT, and even custom kernels
• Working closely with research, platform, and product teams to deliver new features and enhance the developer experience
• Identifying and resolving bottlenecks through profiling, benchmarking, and performance tuning
• Helping to define best practices for building, testing, and maintaining production ML services and APIs
• Mentoring other engineers and helping to foster a culture of technical excellence and innovation

What our client is looking for

• 7+ years of experience building and deploying large-scale ML systems in production
• Strong Python and PyTorch skills, with a deep understanding of transformers, LLMs, and multimodal models
• Hands-on experience with distributed training frameworks like DeepSpeed or FSDP
• Solid background in GPU programming (CUDA, ROCm) and inference optimisation
• Practical experience with parameter-efficient fine-tuning techniques in real-world applications
• Familiarity with container orchestration tools (Kubernetes, Kubeflow) and cloud-native environments
• Knowledge of serving frameworks like Triton, vLLM, or similar
• Clean, maintainable coding style and a strong testing discipline
• Great communication skills and a collaborative mindset

For more information contact Cam Dalziel, , or apply today.