Senior AI Engineer (Production GenAI and ML Systems)

SATS Ltd.; Singapore; On-site; SGD 140,000 - 200,000; Full time

Job summary

SATS Ltd. is seeking a Senior AI Engineer to build and scale production-grade AI/ML systems within the AI Centre of Excellence. The role focuses on deploying, monitoring, and maintaining GenAI, simulation, and search capabilities across enterprise platforms.

You will work to bridge data science and engineering, delivering reliable AI services, scalable pipelines, and reusable GenAI components while driving adoption across teams.

Qualifications

• Bachelor/MSc/PhD in CS, Math or related field.
• 6–10 years of ML engineering or software engineering.
• Strong Python and FastAPI proficiency.
• Expertise in Docker, Kubernetes, MLflow/Kubeflow, and CI/CD pipelines.

Responsibilities

• Design and scale production-grade ML pipelines (batch & real-time).
• Build model serving infrastructure via APIs and microservices.
• Implement CI/CD for ML workflows and manage datasets/models.
• Collaborate with AI CoE and platform teams for scalability.
• Enable rapid experimentation and GenAI adoption.

Skills

Python

FastAPI

ML engineering

Software engineering

Education

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

Tools

Docker

Kubernetes

MLflow

Kubeflow

CI/CD pipelines

Job description

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.

• Design and implement scalable ML pipelines (batch & real-time)
• Build model serving infrastructure using APIs and microservices
• Optimize inference performance and latency

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.