Senior AI Platform System Engineer

About this role

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 Design, develop, test, and maintain scalable, secure, and reliable AI/ML infrastructure for enterprise software running on Kubernetes and microservices.

Develop reusable frameworks and components for AI model training and inference across different customer environments. Build and maintain automated MLOps pipelines for model training, testing, deployment, and monitoring using technologies such as MLflow and Spark. Integrate AI/ML services with backend systems, event-driven architectures, APIs, and data pipelines using technologies such as Kafka, gRPC, and REST. Optimize model deployment and serving for performance, latency, throughput, and resource utilization, including isolated environments with limited connectivity and varying GPU availability.

Improve platform architecture, deployment automation, Helm charts, and DevOps workflows to ensure scalability, reliability, and security in line with ISO 27001 requirements. Support customer deployments by contributing to technical design decisions, providing configuration guidance and training, and sharing operational best practices. Requirements Degree in Computer Science, Platform Engineering, or a related field, or equivalent practical experience.

5+ years of hands-on experience in AI/ML platform engineering. Strong experience with Kubernetes, distributed systems, data engineering, and AI/ML platforms, including Spark and vLLM or similar technologies. Good understanding of MLOps, including automated model training, testing, deployment, and monitoring. Familiarity with MLflow and PyTorch is expected. 2+ years of experience deploying AI/ML platforms in isolated or non-SaaS environments, ideally in production.