AI Platform Engineer

Responsibilities

1. Contribute to the development of AI/ML platforms, including monitoring, logging, and deployment of proprietary, open-source, or internally developed applications.
2. Design and develop services, and integrate them with both internal and external APIs.
3. Identify and assess emerging technologies that enhance the performance, maintainability, and scalability of the infrastructure.
4. Deliver clear visibility into the architecture, operational state, and performance of the AI/ML platform.
5. Collaborate closely with Architects, Platform Engineers, and Product Owners to deliver software in a continuous delivery environment.
6. Partner with data scientists and business stakeholders to support the development and deployment of analytics and machine learning models.

Qualifications

• University degree in Computer Science, Software Engineering, or a related field
• At least 3 years of experience in AI/ML platform development
• Strong background in software engineering and system design (required)
• Hands-on programming experience in Python
• Experience with DataOps/MLOps in a large-scale enterprise environment (preferred)
• Experience delivering large-scale data infrastructure (hundreds of TB) (preferred)
• Experience with public cloud platforms (AWS, Azure, AliCloud) (preferred)
• Familiarity with the following technology stack:
  • Infrastructure: Docker, Terraform, Kubernetes
  • Observability: Grafana, Loki, Prometheus
  • AI/ML Platform: Jupyter, MLflow, Ray, vLLM
  • DevSecOps Suite: Jenkins, JIRA, Sonar, Git, Ansible, Nexus, Harbor
  • Test Frameworks: jMeter, jUnit, PyTest
• Experience working in an international team with a solid understanding of the financial services industry (a plus)
• Excellent communication skills and a data-driven mindset
• Strong team management and problem-solving abilities; self-motivated, creative, with a proven track record of developing and driving firm-wide initiatives