The AI & Data Analytics Strategic Technology Centre (AI.DA STC) is a corporate applied research lab that aims to develop key technologies to support ST Engineerings global growth plans across all our business sectors.
We seek a driven and passionate individual who can support the team in tackling complex challenges, including designing, implementing, and ensuring the delivery of end-to-end AI/ML systems for clients and relevant stakeholders.
Responsibilities:
- Develop, maintain, and monitor scalable pipelines and machine learning workflows across various platforms
- Design and develop backend and frontend components to enable seamless integration and interaction between differing components of an AI/ML product or application.
- Create and manage environments for AI development and production, ensuring optimal resource allocation and compliance with security standards.
- Implement continuous monitoring mechanisms for AI solutions to ensure performance efficiency, accuracy, and reliability.
- Collaborate with cross-functional teams to implement best practices in code development, data governance, and automated pipelines.
- Contribute to the architecture and advancement of the data and analytics platform, exploring new tools and techniques within distributed environments.
- Integrate and transform data from diverse sources, such as databases, APIs, log files, and streaming platforms to support analytics and machine learning operations.
- Partner with stakeholders to develop solutions using AI/ML, tailored to business needs, ensuring the seamless integration of differing capabilities.
Requirements:
- Experienced in software engineering, with 3+ years of experience in roles that involve the intersection of AI/ML, data engineering, and/or system administration.
- Proven expertise in building scalable solutions.
- Experience with and knowledge of the following:
- Linux and Unix-based operating systems
- Version control systems (Git)
- Containerisation tools (Docker, podman, buildah)
- virtual environments/machines and dependency management
- DevOps-related skills (CI/CD, testing, automated pipelines, packaging, etc.)
- MLOps concepts and tooling (experiment tracking, lineage tracking, data versioning, model deployment, etc.).
- Observability (Logs, Metrics, Traces, etc.)
- Networking concepts
- Infrastructure as Code frameworks/workflows
- Proficiency and hands-on experience in Python and SQL. Familiarity with Typescript or Go would be advantageous.
- Experience and familiarity with distributed tooling.
- Ability to develop and maintain deployments/services within a Kubernetes environment. Familiarity with tools relevant to the Kubernetes ecosystem is expected.
- Experience with batch data processing and data modeling. Familiarity with real-time implementations would be advantageous.
- Understanding and awareness of software and AI engineering best practices.
- Exposure to the Generative AI ecosystem.
- Analytical, problem-solving, and communication skills.
