Software Engineer (Hybrid Remote)

buscojobs España; Madrid; A distancia; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

Join a leading company to revolutionize the AI industry by designing scalable MLOps pipelines and deploying advanced models. Collaborate with a global team to enhance client strategies and mentor junior members. This role offers a chance to significantly impact AI-driven projects.

Formación

• 5+ years of hands-on experience in MLOps, DevOps, or ML Engineering roles.
• Proficiency with cloud platforms like AWS, GCP, Azure.

Responsabilidades

• Design and deploy scalable MLOps pipelines optimized for GenAI applications.
• Implement and fine-tune advanced models like GPT in production environments.

Conocimientos

Python

MLOps

DevOps

Machine Learning

Cloud Platforms

Educación

Bachelor's or Master's degree in Computer Science

Herramientas

TensorFlow

PyTorch

Docker

Kubernetes

Databricks

Descripción del empleo

Help to revolutionise a fast-moving industry with cutting-edge AI : Our client is a globally recognised brand with deep-rooted expertise. You'll join a global team with a distributed set of skills including Research, Applied AI and Engineering.

This isn't just another engineering role – it's an opportunity to pioneer systems that transform how companies connect with their customers

Your expertise will directly influence how some of the world's leading brands enhance their strategies.

Production-Ready GenAI Infrastructure : Design and deploy scalable MLOps pipelines specifically optimized for GenAI applications and large language models

State-of-the-Art Model Deployment : Implement and fine-tune advanced models like GPT and similar architectures in production environments

Hybrid AI Systems : Build robust CI / CD pipelines for ML, enabling seamless testing, validation, and deployment

Cost-Efficient Cloud Infrastructure : Optimize cloud resources to maximize performance while maintaining cost efficiency

Governance and Versioning Systems : Establish best practices for model versioning, reproducibility, and responsible AI deployment

Integrated Data Pipelines : Utilize Databricks to construct and manage sophisticated data and ML pipelines

Implement comprehensive monitoring systems to ensure reliability and performance

5+ years of hands-on experience in MLOps, DevOps, or ML Engineering roles

Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face)

Strong cloud platform experience (AWS, GCP, Azure) and managed AI / ML services

Practical experience with Docker, Kubernetes, and container orchestration

Databricks expertise, including ML workflows and data pipeline integration

Familiarity with MLflow, DVC, Prometheus, and Grafana for versioning and monitoring

Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience)

Fluency in written and spoken English

You enjoy mentoring junior team members and elevating the entire technical organization

You'll be working with a modern data stack designed to process large-scale information, automate analysis pipelines, and integrate seamlessly with AI-driven workflows. This is your chance to make a significant impact on projects that push the boundaries of AI-powered insights and automation in industry.

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