Related skills
docker aws python kubernetes tensorflow📋 Description
- Collaboration with data scientists to implement models.
- Architect scalable ML systems and infrastructure.
- Monitor and optimize models in production.
- Develop APIs to integrate models with systems.
- Lead ML Platform evolution and CI/CD improvements.
- Bridge data science and engineering communication.
🎯 Requirements
- Degree in Computer Science, Engineering, or related field.
- More than 2 years of experience in technical ML roles with software engineering emphasis.
- Proficiency in Python.
- Experience with ML frameworks: MLflow, TensorFlow, PyTorch.
- Cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes); Kubernetes deployment required.
- Strong problem-solving and teamwork; excellent communication.
🎁 Benefits
- Collaborative, innovative environment with impact
- Cutting-edge ML projects and career growth
- Continuous learning and skill development
- Recharge days: 10 Fridays annually
- Madrid office with flexible hours
- 3 weeks full remote every six months
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