Machine Learning Engineer

We're building intelligent systems that push the boundaries of what's possible with language and sequence modelling. As our new ML Engineer, you'll own the full lifecycle — from research and experimentation to production deployment — of transformer-based models at scale.

What you'll do

• Design, fine-tune, and evaluate large-scale transformer architectures (BERT, GPT, T5, and beyond)
• Lead end-to-end ML pipelines: data curation, training, optimisation, and serving
• Apply techniques such as LoRA, RLHF, and quantisation to improve model efficiency and alignment
• Collaborate with product and infrastructure teams to ship models that solve real-world problems
• Stay current with research; translate papers into practical, production-ready implementations

What we're looking for

• 3+ years of hands‑on experience with transformer-based models in NLP, CV, or multi‑modal settings
• Strong proficiency in Python; deep familiarity with PyTorch and the Hugging Face ecosystem
• Solid understanding of attention mechanisms, positional encodings, and training dynamics
• Experience deploying models to production (e.g. via ONNX, TorchServe, vLLM, or similar)
• Bonus: publications, open‑source contributions, or experience with distributed training (e.g. DeepSpeed, FSDP)