Senior ML Engineer: LLMs, RAG, Multi-Agent AI - Hybrid

Tamarind Intelligence; Madrid; Híbrido; EUR 70.000 - 110.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Private health insurance

Employee stock purchase plan

Paid sick leave

Referral program

Professional certification

Language courses

Descripción de la vacante

EPAM is seeking a Senior ML Engineer to join our Madrid team in a hybrid mode. You will design, build, and deploy scalable ML and AI solutions powering enterprise digital capabilities for a leading wealth management organization.

Work across the full lifecycle from concept to production in an agile DevOps environment with cross-functional teams. You will focus on Large Language Models, multi‑agent workflows, and production-grade ML practices, shaping AI-driven innovation within a global firm

Formación

• Bachelor's or Master's degree in a data science/CS/math-related field.
• Proven experience as a ML Engineer or similar role.
• Strong Python programming and ML framework experience (TensorFlow or PyTorch).
• Experience deploying LLMs and orchestration frameworks.

Responsabilidades

• Design, develop, deploy, and optimize ML/AI solutions for enterprise use.
• Build multi-agent systems and enable AI models with function/tool calling capabilities.
• Design and maintain RAG systems grounding outputs in enterprise data.
• Fine-tune LLMs for performance and reliability.
• Collaborate with data engineers, platform teams, and data scientists to integrate ML into systems.
• Conduct code reviews, testing and ensure best practices.

Conocimientos

Python

ML engineering

Agile

DevOps

Educación

Bachelor's or Master's in Data Science/CS/Math

Herramientas

TensorFlow

PyTorch

Kubernetes

Descripción del empleo

EPAM is seeking a Senior ML Engineer to join our Madrid team in a hybrid mode. You will design, build, and deploy scalable ML and AI solutions powering enterprise digital capabilities for a leading wealth management organization.

Work across the full lifecycle from concept to production in an agile DevOps environment with cross-functional teams. You will focus on Large Language Models, multi‑agent workflows, and production-grade ML practices, shaping AI-driven innovation within a global firm