At a Glance
- Tasks: Build AI/ML solutions for aviation maintenance and operations using real operational data.
- Company: Join a global leader in aviation software with a focus on innovation.
- Benefits: Shape the future of aviation tech while enjoying competitive pay and growth opportunities.
- Other info: Dynamic work environment with a chance to influence global aviation operations.
- Why this job: Make a real impact in aviation by solving complex problems with cutting-edge AI technology.
- Qualifications: Experience in AI systems, machine learning, and Python development is essential.
The predicted salary is between 60000 - 80000 € per year.
We're building production AI/ML capabilities into aviation maintenance and operations software used globally by airlines, MROs, and CAMOs. You'll work on real problems with real operational data — predicting component failures, surfacing anomalies in live operations, mining decades of maintenance records, and getting models to run reliably in environments where downtime affects flight schedules. This is hands-on engineering: model development, data pipelines, deployment, and monitoring.
About OASES: Our Aviation group delivers mission-critical software solutions that empower airlines, airports, and aviation service providers to operate efficiently and safely. From maintenance planning and flight operations to compliance and resource management, our products enable customers to optimize performance, reduce costs, and ensure regulatory compliance.
Key Responsibilities:
- Predictive maintenance — remaining-useful-life models for components, failure prediction from sensor and event data.
- Anomaly detection — surfacing operational deviations across fleets in real time.
- Maintenance NLP — extracting structured signal from years of free-text maintenance logs and defect reports.
- Operational forecasting — parts demand, planning load, workflow bottlenecks.
- AI-assisted knowledge access — RAG and search over technical manuals, regulatory documentation, and internal operational knowledge.
- Productionisation — getting all the above to run reliably, observably, and at scale.
Requirements: We are looking for someone who understands how AI systems are built — not only how AI tools are used. Strong experience in several of the following areas:
- Machine learning model development and training.
- Time-series analysis and predictive analytics.
- LLMs, RAG pipelines, and vector search.
- Operational telemetry and data pipelines.
- MLOps and scalable AI deployment.
- Python and backend engineering.
- API and distributed systems design.
Strong advantages: aviation, predictive maintenance, industrial IoT, time-series forecasting at scale, or production LLM deployment. We are looking for an engineer capable of building operational AI systems that:
- Learn from operational data.
- Improve real-time decision-making.
- Integrate into production aviation workflows.
- Scale reliably in operational environments.
Benefits: This is an opportunity to help shape the future of operational aviation software and real-time operational intelligence across a global aviation software portfolio.
Senior Applied AI/ML Engineer employer: Valsoft Corporation
At Valsoft, we pride ourselves on being an excellent employer by fostering a dynamic work culture that encourages innovation and collaboration. As a Senior Applied AI/ML Engineer, you'll have the opportunity to work on impactful projects that shape the future of aviation software while benefiting from extensive employee growth opportunities and a supportive environment that values your contributions. Our global presence allows for unique networking opportunities and the chance to be part of a mission-driven team dedicated to enhancing operational efficiency in the aviation industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Applied AI/ML Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the aviation and AI/ML space. Attend meetups, webinars, or industry conferences. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to predictive maintenance or anomaly detection. This will give potential employers a taste of what you can do and how you tackle real-world problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and backend engineering skills. Be ready to discuss your experience with MLOps and scalable AI deployment. Practice coding challenges and system design questions to impress the interviewers.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who can help us shape the future of operational aviation software. Your next big opportunity could be just a click away!
We think you need these skills to ace Senior Applied AI/ML Engineer
Some tips for your application 🫡
Show Your Passion for AI/ML:When writing your application, let us see your enthusiasm for AI and machine learning! Share specific projects or experiences that highlight your hands-on engineering skills and how they relate to the aviation industry.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for this role. Highlight relevant experience in predictive maintenance, anomaly detection, and operational forecasting. We want to see how your background aligns with our mission at StudySmarter!
Be Clear and Concise:Keep your application straightforward and to the point. Use clear language to describe your skills and experiences. We appreciate a well-structured application that makes it easy for us to see why you’re a great fit for the Senior Applied AI/ML Engineer role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the position. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Valsoft Corporation
✨Know Your AI/ML Stuff
Make sure you brush up on your knowledge of machine learning model development, predictive maintenance, and time-series analysis. Be ready to discuss specific projects you've worked on that relate to these areas, as they’ll want to see how you can apply your skills to real-world problems in aviation.
✨Showcase Your Hands-On Experience
Since this role is all about hands-on engineering, be prepared to talk about your experience with data pipelines, deployment, and monitoring. Bring examples of how you've successfully productionised models and ensured they run reliably in operational environments.
✨Understand the Aviation Context
Familiarise yourself with the aviation industry, especially around predictive maintenance and operational workflows. Knowing how your work can impact flight schedules and safety will show that you’re not just technically skilled but also understand the bigger picture.
✨Ask Insightful Questions
Prepare some thoughtful questions about their current projects or challenges they face in AI/ML within aviation. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
