Descripción de la oferta
Descripción del trabajo
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
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