At a Glance
- Tasks: Build AI/ML solutions for aviation maintenance and operations using real data.
- Company: Join a global leader in aviation software with a focus on innovation.
- Benefits: Enjoy competitive pay, remote work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with excellent career advancement potential.
- Why this job: Make a real impact in aviation by solving complex operational challenges.
- Qualifications: Experience in AI systems, machine learning, and Python programming required.
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.
Why Join Us: This is an opportunity to help shape the future of operational aviation software and real-time operational intelligence across a global aviation software portfolio.
Remote Senior Applied AI/ML Engineer employer: Valsoft Corporation
At Valsoft Corp, we pride ourselves on being an excellent employer by fostering a dynamic and entrepreneurial work culture that empowers our employees to innovate and excel in their roles. As a Remote Senior Applied AI/ML Engineer, you will have the opportunity to work on impactful projects that directly enhance aviation operations, while benefiting from extensive professional growth opportunities and collaboration with a global network of experts. Our commitment to investing in our people and providing a supportive environment ensures that you can thrive both personally and professionally in this exciting field.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Applied AI/ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the aviation and AI/ML space on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about sliding into DMs. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to predictive maintenance or anomaly detection. Use GitHub to share your code and document your thought process. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around MLOps and scalable AI deployment. Practice explaining complex concepts in simple terms, as you’ll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are ready to dive into hands-on engineering. Your next big opportunity could be just a click away!
We think you need these skills to ace Remote Senior Applied AI/ML Engineer
Some tips for your application 🫡
Show Your Passion for AI/ML:When you're writing your application, let your enthusiasm for AI and machine learning shine through! We want to see how you connect with the real-world problems we're tackling in aviation. Share any relevant projects or experiences that highlight your hands-on engineering skills.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for this role. Highlight your experience with predictive maintenance, anomaly detection, and MLOps. We love seeing candidates who can directly relate their skills to what we do at StudySmarter, so don’t hold back!
Be Clear and Concise:Keep your application clear and to the point. We appreciate straightforward communication, especially when it comes to technical details. Use bullet points where possible to make your achievements stand out and ensure we can easily see your qualifications.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do and how you can fit into 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 AI systems, especially in the context of aviation. Be ready to discuss your experience with machine learning model development, predictive maintenance, and time-series analysis. They’ll want to see that you can not only use AI tools but also understand how they’re built.
✨Showcase Your Hands-On Experience
Since this role is all about hands-on engineering, prepare to share specific examples of projects where you've developed models, built data pipelines, or deployed AI solutions. Highlight any experience you have with operational telemetry and MLOps, as these will be key areas of interest.
✨Understand the Aviation Context
Familiarise yourself with the aviation industry and the challenges it faces, particularly around maintenance and operations. Being able to speak knowledgeably about how AI can improve decision-making and efficiency in this sector will set you apart from other candidates.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your understanding of distributed systems design, API development, and scalable AI deployment. Practice explaining complex concepts clearly and concisely, as you may need to demonstrate your thought process during the interview.
