Deploy, tune and create AI/ML models with customers and share critical feature requests with the product and engineering teams
Design, build and own AI/ML products in collaboration with UX, product management and engineering and appropriately prioritize feature roadmaps based on market and customer feedback
Design, implement, test, maintain, improve and monitor AI/ML models for our enterprise software solution based on a our leading training and inference framework running on Kubernetes
Work across the entire model operations stack to create scaleable and traceable model training and inference workloads including model validation pipelines and respective data assets
Leverage modern AI/ML lifecycle technologies (MLFlow, Nvidia NeMo, Ray and Torch Distributor) and integrate with scalable data pipelines (Spark)
Drive the evolution of our architecture and technology stack, ensuring scalability, performance, reliability and security at ISO 27001 level
Support the deployment, monitoring, and optimization of models in complex and varied production environments, including air-gaped product usage scenarios with or without GPU availability
Contribute to model and data pipeline design decisions to ensure the customer deployed Kubernetes stack reliability

University degree in Computer Science, Engineering, or equivalent work experience
5+ years of hands-on AI/ML model engineering experience, incl. LLM fine-tuneing, GNN design and data engineering technologies
Experience in security sensitive product deployment scenarios such as health, defense, intelligence or finance is an advantage
Strong understanding of distributed system design, AI platforms (LangChain, NeMo, PyTorch, SparkML), and MLops practices including MLFlow and Kubernetes
Experienced in writing clean, maintainable, model, applying principles such as clean architecture, agile methodologies, cloud-native development Kubernetes, and modern software engineering practices
Familiarity with our ML/AI stack (Spark, MLFlow, Delta Lake, PyTorch incl. Distributed, TensorFlow, ONNX) and backend technologies such as Helm and Kubernetes is a strong asset
Initial experience managing a product lifecycle and engineering to adoption metrics (users, queries, NPS) or experience in AFC/FCC settings is desired
Ability to collaborate effectively within cross-functional and across customer and internal teams
Excellent problem-solving, debugging, and troubleshooting skills
Strong verbal and written communication skills in English

Make the world safer: Help prevent financial crime and support our customers in creating a safer world
Be part of a leading RegTech: Contribute to a well-established, innovative company in Switzerland
International exposure: Work with global clients on diverse, challenging projects in a multicultural team
Ownership and growth: Take responsibility from day one and develop your skills and career
Flexible work environment: Enjoy hybrid work and flexible hours
Paid education: Access opportunities for further training to enhance your expertise

Forward Deployed AI/ML Model Engineer

Key skills