machine learning engineer for airline safety

SafetyManager365 helps airline safety teams analyze safety reports, operational data and investigations, identify risks earlier, and make better operational decisions.

• Own ML initiatives end to end, from understanding customer problems and designing experiments to implementation, deployment, measurement and continuous improvement;
• Evaluate ML and AI technologies with a product mindset, choosing pragmatic solutions that deliver customer and business value;
• Partner with product managers and engineers to design and deliver robust, production-ready ML and AI solutions;
• Write clean, efficient and maintainable code and uphold high quality standards;
• Collaborate through regular pair programming, share knowledge, support colleagues and improve engineering practices;
• Provide technical leadership for machine learning initiatives, owning work from problem definition and experimentation through production delivery;
• Coach and mentor engineers, raising ML capability through pairing, knowledge sharing and technical guidance.

• At least 8 years of relevant professional machine learning experience, including substantial hands-on experience building and operating ML products in production;
• Strong practical foundation in machine learning and software engineering;
• Take a pragmatic, iterative approach to ML development, running small, time-boxed experiments and adapting based on evidence;
• Excellent analytical skills and practical understanding of machine learning and statistics, with a focus on text-based (NLP) models;
• Superior knowledge of Python and the PyData ecosystem, including pandas, scikit-learn, pytorch / tensorflow, and MLOps frameworks such as MLFlow, Weights & Biases or similar;
• Proven expertise with Large Language Models (LLMs) and developing agentic AI applications;
• Extensive hands-on experience designing, building, deploying and operating production ML systems, including data/ML pipelines, model evaluation, observability and productisation in a cloud environment;
• Excellent communication, self-awareness and interpersonal skills; able to challenge ideas constructively, navigate disagreement with confidence and empathy, and build trust across a collaborative team;
• Strong software engineering fundamentals and experience designing and evolving production systems, with sound architecture and engineering trade-offs;
• Nice to have: experience with PydanticAI, a passion for the aviation industry and a desire to use AI to improve airline safety.

• Salary range: €110-€130K annually, depending on experience;
• Full-time role, 40 hours per week, with core hours from 10am to 5pm and flexibility outside those hours;
• Annual team offsite and access to offices in Europe and a co-working space in your location;
• High-end equipment;
• Learning & Development budget for industry events and professional courses;
• Hybrid-remote work policy.