Senior ML Engineer, LLM Systems & Evaluation

Grid Dynamics; Marbella; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Grid Dynamics is seeking a Senior Machine Learning Engineer to lead development of LLM-based systems and evaluation frameworks in Marbella. You will own ML projects end-to-end, designing benchmarks, datasets, and metrics to measure model performance and safety.

You will work with product and engineering teams to translate business goals into measurable ML objectives, apply RAG and agentic techniques, and help shape scalable ML pipelines and tooling.

Formación

• 5+ years of experience in ML engineering or related field.
• Strong fundamentals in ML and model evaluation.
• Expert Python and ML framework experience.
• Knowledge of RAG, agentic systems and LLM safety concepts.
• Experience training or fine-tuning models.
• Experience with LLMs beyond API usage.
• Ability to translate results into actionable recommendations.
• Ability to build and maintain ML pipelines and tooling.
• Strong communication skills.

Responsabilidades

• Own ML projects from problem definition through implementation.
• Design and implement evaluation methodologies for AI/ML systems.
• Create datasets, benchmarks, and metrics to measure performance.
• Evaluate and improve LLM-based systems including RAG and agents.
• Analyse model behaviour and identify failure modes.
• Build and maintain ML pipelines and evaluation infra.
• Collaborate with product, engineering, and research teams.
• Prototype and iterate to solve business challenges.
• Communicate findings and recommendations to stakeholders.

Conocimientos

5+ years

Strong Python

PyTorch

TensorFlow

JAX

RAG concepts

LLM safety concepts

model evaluation

AI systems design

communication skills

Herramientas

PyTorch

TensorFlow

JAX

Descripción del empleo

Grid Dynamics is seeking a Senior Machine Learning Engineer to lead development of LLM-based systems and evaluation frameworks in Marbella. You will own ML projects end-to-end, designing benchmarks, datasets, and metrics to measure model performance and safety.

You will work with product and engineering teams to translate business goals into measurable ML objectives, apply RAG and agentic techniques, and help shape scalable ML pipelines and tooling.