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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in machine learning and software engineering, with a strong focus on building and deploying production-ready ML systems. Capable of providing technical leadership, mentoring engineers, and fostering collaboration to enhance ML capabilities.
Highest-signal resume keywords
Machine Learning ExpertisePython ProgrammingMLOps FrameworksNLP Model DevelopmentProduction System Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningSoftware EngineeringData PipelinesModel EvaluationCloud Environment DeploymentStatistical AnalysisText-Based ModelsExperimentation DesignContinuous ImprovementArchitecture Trade-Offs
Soft Skills
Excellent CommunicationInterpersonal SkillsSelf-AwarenessConstructive ChallengeEmpathy
Tools & Technologies
PythonPyData EcosystemPandasScikit-LearnPyTorchTensorFlowMLflowWeights & Biases
Industry Keywords
Aviation IndustryAI TechnologyCustomer ValueProduct MindsetTechnical Leadership
Tech Stack
Tools & technologiesCloudPandasPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Own ML initiatives end to end, from understanding customer problems and designing experiments through implementation, deployment, measurement and continuous improvement
- Evaluate ML and AI technologies with a strong product mindset, prioritizing 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 using strong software engineering practices
- Work collaboratively through regular pair programming, knowledge sharing and continuous improvement of engineering practices
- Provide technical leadership for machine learning initiatives from problem definition and experimentation through production delivery
- Coach and mentor engineers, raising ML capability through pairing, knowledge sharing and technical guidance
Requirements
What you’ll need- At least 8 years of relevant professional machine learning experience
- Substantial hands-on expertise building and operating ML products in production
- Solid practical foundation in machine learning and software engineering
- Scientific education in computer science, machine learning or a related discipline is welcome, but equivalent industry experience is also valued
- Pragmatic, iterative approach to ML development
- 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
- Knowledge of MLOps frameworks such as MLflow and Weights & Biases or similar
- Extensive hands-on experience designing, building, deploying and operating production ML systems
- Experience with data/ML pipelines, model evaluation, observability and productization in a cloud environment
- Strong software engineering fundamentals and experience designing and evolving production systems
- Ability to make sound architecture and engineering trade-offs
- Excellent communication, self-awareness and interpersonal skills
- Ability to challenge technical ideas constructively, navigate disagreement with confidence and empathy, and build trust
- Passion for the aviation industry and desire to leverage AI technology to improve airline safety
Benefits
Comp & perks- High-end equipment to facilitate your best work
- Competitive salary and benefits package
- Annual team offsite
- Access to offices in Europe
- Co-working space in your location
- Hybrid-remote work policy