An opportunity for an Machine Learning Engineer has arisen within Airbus Helicopters (Albacete, Spain). QUALITY & CONVENIENCE - This modern urban center, known for its rich cultural heritage, and it is conveniently close to Madrid and the Mediterranean coast. As a strategic Center of Excellence, we are a global leader in helicopter production, offering you endless potential to grow alongside our major projects.

THE PROJECT: Welcome to the Digital Campus , a pioneering ecosystem dedicated to industrial digitalization and innovation. Bring your ideas to a dynamic, modern ecosystem and help us build the next generation of aerospace solutions. You will join the Digital Innovation Team within Airbus Helicopters' Transformation Department.

Our mission is to bridge the gap between applied research and concrete business value, leveraging technologies like Artificial Intelligence, Advanced Analytics, and Mixed Reality. While you will be the core representative of our Digital Innovation team in Albacete, you will work in a deeply integrated, international environment with our hubs in Marignane (France) and Donauwörth (Germany). Being physically located alongside the Albacete IT teams, you will act as a strategic bridge to ensure our AI innovations are robustly integrated and scaled into enterprise systems.

We are looking for a Machine Learning Engineer to help bridge the gap between our Data Science Proof of Value (PoVs) and enterprise-scale production. This is not an exploratory Data Science or pure modeling role. We are looking for a robust hands‐on software and ML engineer who understands IT infrastructure, CI/CD, and how to scale AI solutions securely.

You will leverage your technical expertise to collaborate with local IT teams, helping to design practical, scalable solutions for deploying AI projects (e.g., Alongside this cross‐functional integration work,



you will also provide hands‐on platform support and tooling for our internal Data Scientists.

Industrialization & CI/CD: Collaborate with IT teams to define and implement best practices for transitioning ML models from PoV to production on OpenShift (On‐Premise) and GCP. Build, maintain, and improve CI/CD pipelines to ensure code quality and secure deployments. This includes managing complex data ingestion pipelines for RAG architectures, using search engines, and working with vector and graph databases.

Monitoring & Resource Optimization: Set up dashboards to monitor model health, API performance, and detect data drift.

Platform

Support & "Starter Kits": Streamline the work of our Data Science team by creating standardized, ready‐to‐use templates (Docker/Git) for new PoVs, maintaining optimized environments, and resolving complex dependency issues. You will translate Data Science compute needs into IT architecture specifications and ensure our projects comply with strict cybersecurity standards.

Infrastructure: OpenShift AI (On‐Premise) as a primary environment, with GCP for cloud deployments. Docker, Kubernetes.

Databases & Search: PostgreSQL (including pgvector), Elasticsearch, and Graph Databases (em. Neo4j). Python (Advanced) and standard software engineering practices (OOP, APIs with FastAPI).

MLOps & CI/CD: MLflow, Git, GitLab CI/CD (or similar).

AI/Data Science Tools: Pandas, Scikit‐Learn, Streamlit, GenAI integration frameworks (LangChain, etc.), and monitoring tools (Grafana/Kibana).

Experience: 3 to 4+ years of full‐time,



post‐graduate industry experience in Machine Learning Engineering, MLOps, or Software Engineering.

Please note: while we highly value internships, apprenticeships, and academic projects, this specific role requires an established track record in a corporate/enterprise environment. We would be delighted to read, at the top of your resume or cover letter, a brief example of a ML model or Gen AI solution you have put into production. Master's degree or equivalent in Computer Science, Software Engineering, or Artificial Intelligence.

You thrive in bridging the gap between Data Science (algorithmic focus) and IT (production and infrastructure focus). Fluency in English and Spanish is mandatory to collaborate effectively across our international hubs and local IT teams. (French or German is a plus).

Mobility: Open to occasional travel to Marignane and Donauwörth to align on global AI strategies.

Hybrid model of working : we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster adaptable working arrangements to stimulate innovative thinking. Collective transport service subject to working calendar/home location.

Benefits such as life insurance, health insurance, employee stock options, retirement plan, or study grants. On‐site facilities (among others): free canteen, kindergarten, medical office. Possibility to collaborate in different social and corporate social responsibility initiatives .

Permanent Digital

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

📌 Machine Learning Engineer - Hybrid Remote (Albacete)
🏢 Airbus Helicopters
📍 Albacete