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# AI & ML Engineer

- **Company:** Mane Flavor & Fragrance Manufacturer
- **Location:** Barcelona, Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, DataOps, Azure Machine Learning, Software Deployment, Delivery Pipeline, Containerization, Information Technology, Machine Learning Operations, Docker, Databricks
- **Published:** July 13, 2026
- **Apply:** https://www.jobleads.com/es/job/e95869e4893574e567d48e7f5e4da1f3e

## About the Role

* Experience: More than 5 years of experience in IT or Engineering, including significant hands-on experience in AI/ML and technical leadership.
 * Education: Master's degree or higher in Computer Science, AI, Data Science, or related field.
 * Technical Excellence: Advanced proficiency in Python and strong knowledge of AI/ML algorithms, architectures, and data engineering best practices.
 * MLOps & Cloud: Hands-on experience with Azure ML or Databricks, CI/CD pipelines, Docker, and monitoring of AI systems in production.
 * Collaboration & Communication: Experience working in Agile teams and the ability to clearly communicate technical concepts to both technical and non-technical stakeholders.
 * Languages: Full professional proficiency in English; French is a strong plus.
 * Industry Experience (Preferred): Exposure to formulation, chemistry, or the fragrance & flavor industry.

## Description

As a Senior AI/ML Engineer, you will be a key technical contributor responsible for developing and deploying complex AI initiatives. You will focus on the end-to-end lifecycle of ML solutions-from technical design and coding to production deployment and continuous optimization., * Technical Implementation: Contribute to the design and development of scalable, maintainable AI solutions aligned with modern best practices.

 * Hands-on Development: Deliver high-quality code for data, modeling, and deployment pipelines, leading the team through engineering rigor.
 * MLOps Mastery: Implement and maintain robust MLOps workflows, focusing on automated CI/CD, containerization, and model observability.
 * Agile Delivery: Work within an Agile framework to ensure research translates into predictable production value, meeting project milestones and deadlines.
 * Business Advisory: Partner with technical and business stakeholders to translate business challenges into technical requirements and provide clear project updates. Ensure compliance with data privacy, security and ethical AI guidelines, in collaboration with relevant stakeholders.


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