Senior Machine Learning Engineer

Intellias; Jerez de la Frontera; Presencial; EUR 55.000 - 75.000; Jornada completa

Descripción de la vacante

Join a leading technology company as a Senior Machine Learning Engineer, where you'll create innovative AI-powered systems using advanced ML toolkits. You'll design intelligent agents, integrate large language models, and leverage cloud infrastructure for deployment, all while collaborating in a dynamic team environment. This role requires a strong background in Python, cloud services, and machine learning frameworks to deliver scalable AI solutions.

Formación

• Experience with Google AgentSpace or Agent Development Kit (ADK).
• Proven experience with LLMs and applied machine learning.
• Experience with MLOps practices including CI/CD pipelines.

Responsabilidades

• Design and implement intelligent agents using Google AgentSpace or ADK.
• Integrate Large Language Models (LLMs) into AI systems.
• Build pipelines for agent planning and API integration.

Conocimientos

Python

Machine Learning

Cloud ML Workflows

Generative AI

Collaboration

Educación

Master's or Ph.D. in Computer Science, Mathematics, Data Science

Herramientas

Google Cloud Platform (GCP)

TensorFlow

PyTorch

Docker

Descripción del empleo

We're hiring a Senior Machine Learning Engineer with hands-on experience in Google AgentSpace / Agent Development Kit (ADK) Join Intellias to build next-generation AI-powered systems with one of the most exciting ML toolkits on the market today! We’re looking for a technically strong and innovation-driven Senior ML Engineer to work on LLM-based agents, autonomous task execution, and cloud-native ML applications. What you’ll be doing : Design and implement intelligent agents using Google AgentSpace or ADK Integrate Large Language Models (LLMs) into modular, production-ready AI systems Build pipelines for agent planning, memory, context, and API integration Work closely with a team of ML engineers and software architects to deploy scalable AI services Leverage cloud infrastructure (primarily GCP, optionally Azure) for real-world ML deployment We expect :

Master’s or Ph.D. in Computer Science, Mathematics, Data Science, or a related field. Experience with Google AgentSpace or Agent Development Kit (ADK). Proven experience with LLMs, Generative AI tooling, and applied machine learning. Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow. Hands-on experience with Google Cloud Platform (GCP), especially services like Vertex AI. Familiarity with agent orchestration concepts and cloud-based ML workflows. Experience with MLOps practices, including containerization (Docker) and CI / CD pipelines. Strong communication skills with the ability to collaborate across technical and non-technical teams. Ability to work during Eastern Standard Time (EST) hours. Nice to have :

Exposure to NotebookLM or similar GenAI prototyping tools. Google Cloud Professional Machine Learning Engineer certification. Experience integrating LLM-powered agents into enterprise or healthcare environments.