Senior Machine Learning Engineer

What You'll Be Doing

• Integrate open-source and third-party models into our inference platform
• Lead fine-tuning initiatives (LoRA, adapters, PEFT, domain adaptation)
• Optimise inference workloads for latency, batching, memory efficiency, and throughput
• Benchmark model quality vs cost vs performance across modalities
• Improve inference startup times and stability under high load
• Build evaluation frameworks and internal tooling for model validation
• Work closely with Infrastructure and Backend teams on scalable serving systems
• Monitor production performance and drive continuous optimisation
• Mentor engineers and help raise the ML engineering bar across the team

What We’re Looking For

• Proven experience delivering ML systems to production environments
• Strong, low-level Python skills and deep hands-on experience with PyTorch
• Experience working with diffusion models, LLMs, or multimodal architectures
• Practical experience fine-tuning large models (LoRA, PEFT, adapters, etc.)
• Experience optimizing inference workloads in GPU environments
• Strong understanding of model evaluation, experimentation, and monitoring
• Ability to debug performance, memory, and reliability issues in production
• Strong systems thinking understanding how ML decisions impact infrastructure
• High ownership and comfort operating in a fast-paced startup environment

Nice to have

• Experience with vLLM or custom inference servers
• Experience with Kubernetes or containerised ML workloads
• Experience working in high-throughput distributed systems
• Background in AI media generation (image, video, audio)
• Experience building internal ML tooling or developer-facing APIs
• Experience with kernels in CUDA/C++