Machine Learning Engineer (Product) (Fixed Term Contract)
Core
Build and optimize end-to-end data and model pipelines for large language models (LLMs), focusing on compression, evaluation, and alignment to make AI faster and more accessible.
Role type
Machine Learning Engineer (Product)
Builds
Production-ready LLMs and data pipelines for deep-tech applications
Domain
Artificial Intelligence / Large Language Models / Deep Tech
Deliverable
production ML models
Required skills
Python, PyTorch, NumPy, Pandas, Git, Unit Testing, CI/CD, Data Curation, Dataset Validation, Distributed Compute, GPU Management, Docker, Cloud Orchestration, Language Modelling Concepts, Statistical Testing, Model Compression Techniques
Preferred skills
PhD in CS/Math/Physics, NLP/LLM experience, Foundational LLM building, Task-grounded Evaluation, Multi-node Training Debugging, Pruning/Quantization/NAS, SFT, RLHF/DPO/GRPO
Technologies
PyTorch, NumPy, Pandas, Docker, Kubernetes (implied by cloud orchestration), Git
Responsibilities
Create, source, augment, and validate datasets; Stand up training/fine-tuning/evaluation flows; Design rigorous evaluation frameworks; Scale training and inference using distributed compute; Improve models post-training via SFT and RL methods; Optimize and specialize models using compression techniques; Collaborate with researchers and engineers on model serving and observability.
Seniority
Mid-Senior, hands-on IC
