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SATS Ltd. · Singapore, Singapore

Senior AI Engineer (Production GenAI and ML Systems)

seniorfull timePosted yesterday
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Stack mentioned

microservicesci/cdragllmagentic-aivllmpythonfastapidockerkubernetesmlflowkubeflowgenerative-aiartificial-intelligencedata-sciencea/b-testingvector-databasesmachine-learning

Job Description

We are hiring a Senior AI Engineer in our AI Centre of Excellence (COE). This role is responsible for building and scaling production-grade AI/ML, GenAI, Simulation, Search systems. This role bridges the gap between data science and engineering by ensuring models are deployed, monitored, and maintained reliably in real-world environments.

ML System Engineering

- Design and implement scalable ML pipelines (batch & real-time)

- Build model serving infrastructure using APIs and microservices

- Optimize inference performance and latency

ML Operations & Automation

- Implement CI/CD pipelines for ML workflows

- Manage model versioning, monitoring, and retraining pipelines

- Ensure reproducibility and reliability of ML systems

Platform Integration and Enablement

- Integrate ML systems with enterprise data platforms

- Collaborate with AI CoE teams on platform capabilities

- Enable self-service ML deployment capabilities

- Provide reusable building blocks for AI teams

- Enable rapid experimentation and deployment

- Collaborate with AI/ML teams to accelerate GenAI adoption

GenAI Platform Development

- Build and maintain RAG pipelines and LLM orchestration frameworks

- Develop reusable GenAI services and APIs

- Enable multi-agent and agentic workflows

Infrastructure & Systems

- Implement scalable model serving infrastructure (vLLM, Triton, APIs)

- Manage vector databases and embedding pipelines

- Optimize performance and cost of LLM systems

Innovation

- Evaluate emerging GenAI tools and frameworks

- Drive adoption of best practices in LLMOps

Collaboration

- Work closely with data scientists to productionize models

- Partner with platform teams for scalability and performance

Key Requirements

- Bachelor / MSC / PHD in Computer Science, Mathematics or related field.

- Ongoing commitment to training and professional development in AIML, GenAI, Aviation Domain, Cargo handling, Ground handling milestones, Ground Freight and Food solutions.

- Minimally 6 to 10 years in ML engineering or software engineering.

- Strong Python + FastAPI.

- Strong expertise in: Docker, Kubernetes, MLflow / Kubeflow, CI/CD pipelines.

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