Forward deployed ai/ml model engineer

As a leading global software product company in the field of Compliance & Automation, IMTF Group develops cutting-edge RegTech solutions with a focus on Anti-Money Laundering and Anti-Fraud. We are dedicated to automating manual processes through the use of machine learning and data science, ensuring our clients have the most efficient and effective compliance solutions on the market. We value innovation, excellence, and continuous learning at IMTF Group. We provide a dynamic, collaborative work environment where your ideas will be heard and your skills will be put to the test. If you are passionate about technology and motivated to make a significant impact in the compliance industry, this is the perfect opportunity for you to thrive and advance your career with us. Responsibilities 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 Requirements 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 Benefits 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 At IMTF, we are committed to treating all candidates with respect and equality, regardless of gender, religion, nationality, or any other characteristic. We embrace diversity and inclusion as integral components of our organizational culture, and we welcome candidates from all backgrounds to apply and contribute to our team.