Senior ML Engineer (LLM Systems & Evaluation)

Grid Dynamics; País Vasco; Presencial; EUR 85.000 - 110.000; Jornada completa

Descripción de la vacante

Grid Dynamics seeks a Senior Machine Learning Engineer specializing in LLM Systems & Evaluation to drive end-to-end ML projects, from problem definition to production-ready solutions. You will design robust evaluation methods for AI systems, build datasets and benchmarks, and help shape product strategies with measurable ML objectives.

You will work on RAG applications, agents, safety-focused evaluation, and end-to-end AI products, collaborating with product, engineering, and research teams

Formación

• 5+ years in Machine Learning Engineering or related field.
• Strong understanding of ML fundamentals and model evaluation.
• Proficient in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Experience with LLMs, RAG, agents, and AI safety concepts.

Responsabilidades

• Own ML projects from problem definition through implementation.
• Design evaluation methodologies for AI/ML systems.
• Create datasets, benchmarks, and metrics to measure performance.
• Evaluate and improve LLM-based systems and AI products.
• Build and maintain ML pipelines and evaluation infrastructure.
• Collaborate with product, engineering, and research teams to translate goals into ML objectives.
• Prototype and iterate rapidly to solve business challenges.
• Communicate findings and trade-offs to technical and non-technical stakeholders.

Conocimientos

Machine Learning

Python

PyTorch

TensorFlow

JAX

LLMs

RAG

Model Evaluation

Data Pipelines

Communication

Herramientas

PyTorch

TensorFlow

JAX

Descripción del empleo

Grid Dynamics seeks a Senior Machine Learning Engineer specializing in LLM Systems & Evaluation to drive end-to-end ML projects, from problem definition to production-ready solutions. You will design robust evaluation methods for AI systems, build datasets and benchmarks, and help shape product strategies with measurable ML objectives.

You will work on RAG applications, agents, safety-focused evaluation, and end-to-end AI products, collaborating with product, engineering, and research teams