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: Enjoy competitive pay, remote work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with excellent career advancement opportunities.
- Why this job: Make a real impact in aviation by solving complex problems with cutting-edge technology.
- Qualifications: Experience in AI systems, machine learning, and backend engineering is essential.
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 in Southend-on-Sea employer: Valsoft Corporation
At Valsoft Corp, we pride ourselves on being an excellent employer that fosters a culture of innovation and collaboration. As a Remote Senior Applied AI/ML Engineer, you'll have the opportunity to work on impactful projects that enhance aviation operations while enjoying a flexible work environment that promotes work-life balance. We are committed to your professional growth, offering continuous learning opportunities and the chance to be part of a global network that values entrepreneurial spirit and expertise.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Applied AI/ML Engineer in Southend-on-Sea
✨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. Share your GitHub link when you apply through our website — it’s a great way to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and MLOps knowledge. Practice coding challenges and be ready to discuss your approach to building operational AI systems. We love seeing how you think through problems!
✨Tip Number 4
Don’t forget to follow up after interviews! A quick thank-you email can go a long way. It shows your enthusiasm for the role and keeps you fresh in the interviewers' minds. Plus, it’s just good manners!
We think you need these skills to ace Remote Senior Applied AI/ML Engineer in Southend-on-Sea
Some tips for your application 🫡
Show Your Passion for AI/ML:When writing your application, let your enthusiasm for AI and machine learning shine through. We want to see that you’re not just ticking boxes but genuinely excited about solving real-world problems in aviation with cutting-edge technology.
Tailor Your Experience:Make sure to highlight your relevant experience in AI systems, predictive maintenance, and data pipelines. We’re looking for hands-on engineers, so share specific projects or achievements that demonstrate your skills in these areas.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see how your background aligns with the role without wading through fluff.
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 role. Plus, it shows you’re keen on joining our team at StudySmarter!
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 to impressing them.
✨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 some technical questions during the interview. Brush up on your Python skills, backend engineering concepts, and API design. You might also be asked to solve a problem on the spot, so practice coding challenges related to AI and data processing to feel more confident.
