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 stakeholdersQualifications:- 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 skillsWould 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

Communicate findings, trade-offs, and recommendations to both technical and non-technical stakeholdersQualifications:- 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 skillsWould 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