Machine Learning Engineer - MLOps & AI Integration

Job Description:

An opportunity for an Machine Learning Engineer has arisen within Airbus Helicopters (Albacete, Spain).

WHY JOIN US?

📍 LIFE IN ALBACETE: QUALITY & CONVENIENCE - 

Albacete is a dynamic, historic city in Spain, located in the region of Castilla-La Mancha. This modern urban center, known for its rich cultural heritage, and it is conveniently close to Madrid and the Mediterranean coast.

Forget long commutes. Albacete offers you the great advantage of a “15-minute city": safe, accessible, comfortable and perfectly connected. Enjoy a premium standard of living at a competitive cost, ensuring you have the perfect balance between your career and your personal life.

🚁 AIRBUS HELICOPTERS: GROW WITH US - We offer more than a job; we offer a community. Immerse yourself in a young, collaborative environment that feels like family. 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: SHAPING THE FUTURE - Welcome to the Digital Campus, a pioneering ecosystem dedicated to industrial digitalization and innovation. This is more than just a workplace; it is a technological hub where we define the future of flight. 

Bring your ideas to a dynamic, modern ecosystem and help us build the next generation of aerospace solutions.

About the Team & the Environment

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.

The Role

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., ML models, GenAI/chatbots). Alongside this cross-functional integration work, you will also provide hands-on platform support and tooling for our internal Data Scientists.

Key Responsibilities

• 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. 

• GenAI & AI Integration: Implement the technical integration of AI solutions (such as chatbots, LLMs, or predictive APIs) into existing business applications. 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. Optimize compute resources (CPU/GPU) to ensure cost-efficiency across our infrastructure.

• 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.

• Cross-functional Collaboration: Act as a proactive technical liaison between the international Innovation team (prototyping) and the Albacete IT department (infrastructure). You will translate Data Science compute needs into IT architecture specifications and ensure our projects comply with strict cybersecurity standards.

Tech Stack You Will Use

• Infrastructure: OpenShift AI (On-Premise) as a primary environment, with GCP for cloud deployments.

• Containers & Orchestration: Docker, Kubernetes.

• Databases & Search: PostgreSQL (including pgvector), Elasticsearch, and Graph Databases (e.g., Neo4j). 

• Programming: 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).

Who You Are

• 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.

• Education: Master’s degree or equivalent in Computer Science, Software Engineering, or Artificial Intelligence.

• Mindset: Highly autonomous but a strong team player. You thrive in bridging the gap between Data Science (algorithmic focus) and IT (production and infrastructure focus).

• Languages: 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.

WHICH BENEFITS WILL YOU HAVE AS AIRBUS EMPLOYEE?

At Airbus we are focused on our employees and their welfare. Take a look at some of our social benefits:

• Vacation days plus additional days-off along the year (Apróx. 35 days per year in total).

• Attractive salary.

• Hybrid model of working: we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible 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.

• Excellent upskilling opportunities and great development prospects in a multicultural environment.

• Option to access special rates in products & benefits.

Take your career to a new level and apply online now! 🚁

Since this position is managed transnationally, please submit your documents (CV and/or cover letter) in English.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:

Airbus Helicopters España, SA

Employment Type:

Permanent

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Experience Level:

Professional

Job Family:

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. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to [email protected].

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.