Senior Machine Learning Engineer

We are looking for a talented Senior Machine Learning Engineer - LLM Systems & Evaluation.This is an opportunity to work on next-generation AI systems, including large language models, retrieval-augmented generation, agents, and AI safety-focused evaluation.Essential functions: - Own machine learning projects from problem definition through implementation - Design and implement evaluation methodologies for AI and machine learning systems - Create datasets, benchmarks, and metrics to measure model and product performance - Evaluate and improve LLM-based systems, including RAG applications, agents, safety systems, and end-to-end AI products - Analyse model behaviour, identify failure modes, and recommend practical improvements - Build and maintain ML pipelines, tooling, and evaluation infrastructure - Collaborate with product, engineering, and research teams to translate business goals into measurable ML objectives - Prototype and iterate rapidly to solve business and product challenges - Communicate findings, trade-offs, and recommendations to both technical and non-technical stakeholders Qualifications: - 5+ years of experience in Machine Learning Engineering or a related field.- Strong understanding of machine learning fundamentals and model evaluation - Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX - Understanding of retrieval-augmented generation (RAG), agentic systems, and LLM safety concepts - Experience training, fine-tuning, or adapting machine learning models - Experience working with Large Language Models beyond simple API integration - Experience evaluating AI systems and translating results into actionable recommendations - Experience building and maintaining machine learning systems and pipelines - Ability to work effectively in ambiguous problem spaces with incomplete requirements and limited data - Strong written and verbal communication skills Would be a plus: - Experience designing benchmarks, evaluation frameworks, or automated evaluation systems - Experience with distributed training or large-scale model inference - Experience building reusable ML tooling and internal platforms - Experience with cloud platforms and modern MLOps practices - Experience working on user-facing AI products at scale - Research experience or publications in machine learning or AI-related fields

Strong understanding of machine learning fundamentals and model evaluation - Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX - Understanding of retrieval-augmented generation (RAG), agentic systems, and LLM safety concepts - Experience training, fine-tuning, or adapting machine learning models - Experience working with Large Language Models beyond simple API integration - Experience evaluating AI systems and translating results into actionable recommendations - Experience building and maintaining machine learning systems and pipelines - Ability to work effectively in ambiguous problem spaces with incomplete requirements and limited data - Strong written and verbal communication skills Would be a plus: - Experience designing benchmarks, evaluation frameworks, or automated evaluation systems - Experience with distributed training or large-scale model inference - Experience building reusable ML tooling and internal platforms - Experience with cloud platforms and modern MLOps practices - Experience working on user-facing AI products at scale - Research experience or publications in machine learning or AI-related fields