Descripción de la oferta
Descripción del trabajoWe 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 implementationDesign and implement evaluation methodologies for AI and machine learning systemsCreate datasets, benchmarks, and metrics to measure model and product performanceEvaluate and improve LLM-based systems, including RAG applications, agents, safety systems, and end-to-end AI productsAnalyse model behaviour, identify failure modes, and recommend practical improvementsBuild and maintain ML pipelines, tooling, and evaluation infrastructureCollaborate with product, engineering, and research teams to translate business goals into measurable ML objectivesPrototype and iterate rapidly to solve business and product challengesCommunicate 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 systemsExperience with distributed training or large-scale model inferenceExperience building reusable ML tooling and internal platformsExperience with cloud platforms and modern MLOps practicesExperience working on user-facing AI products at scaleResearch experience or publications in machine learning or AI-related fields
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