The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A Singapore-based global technology, defense, and engineering group with a long history was formally created in December 1997 through the merger of four listed Singaporean companies.
Assistant Principal AI Engineer – MLOps, AI.DA STC
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
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.
Nice to Have:
Familiarity with Scrum methodology and agile practices.
Experience with streaming data technologies such as Kafka.
Exposure to the Generative AI-centric ecosystem.
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.
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No Client Relationship: This company is not a client of SpringCube unless stated.
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