AI Engineer

Tech Aalto Pte ltd; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tech Aalto Pte ltd is seeking an AI engineer to bridge research and production, building robust data pipelines, model registries, and production-grade AI integrations. You will work across data scientists and engineers to operationalize models and agentic workflows in real-world systems.

The role focuses on developing, deploying, and scaling ML solutions, managing lifecycle stages, and ensuring reliability, performance, and governance of AI workloads within a fast-paced agile environment.

Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Advanced proficiency in Python programming with clean, testable code.
• DevOps & Containers: Docker and Kubernetes experience.
• Experience with ML lifecycle tooling like MLflow or weights & biases.
• Experience with LLMs and AI agent workflows.

Responsibilities

• Design, develop and deploy ML solutions and services.
• Operationalize end-to-end ML pipelines from data ingestion to training and model serving.
• Operationalize LLMs, embeddings, and multi-agent systems in real-world apps.
• Manage ML lifecycle: experimentation, registry, deployment.
• Oversee model promotion lifecycle with validation gates and approvals.

Skills

Problem solving

Communication

Project management

Continuous learning

Attention to detail

Education

Bachelor's or Master's in Data Science/CS/Math/Stats

Tools

Docker

Kubernetes

MLflow

Weights & Biases

GitLab/Jenkins

Job description

AI engineer

GENERAL DESCRIPTION

We are seeking a skilled machine learning platform engineer (MLOps) to join our agile platform team which is part of our ML & AI ART. In this role, Bridge the gap between experimental data science and production-grade systems. You'll contribute across the entire lifecycle - from concept to deployment - and collaborate closely with cross-functional teams to deliver high-quality digital solutions. Further, you drive the orchestration of advanced agentic workflows to enable autonomous, AI-driven systems. You will be responsible for engineering robust data pipelines, establishing comprehensive model management lifecycles, overseeing all foundational platform-level AI integrations – including engineering a robust library of AI skills for agent use.

kEY FEATURES OF THE POSITION

Functional / Technical

• Design, develop and deploy machine learning solutions and services
• Implement end-to-end machine learning pipelines from data ingestion to training and model serving
• Operationalize LLMs, embeddings, and multi-agent systems in real-world applications
• Manage the machine learning and model lifecycle (experimentation, registry, deployment)
• Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production
• Containerize applications using Docker and orchestrate them via Kubernetes
• Build and maintain CI/CD pipelines for ML models and LLM applications
• Collaborate with data scientists to refactor research code into production-ready Python code
• Monitor model performance, data drift, and performance in production
• Assess and integrate AI solutions ensuring optimal performance and reliability
• Design and implement production grade RAG systems
• Collaborate with infrastructure teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions

SKILLS REQUIREMENTS OF THE POSITION

Competencies

• Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization
• Ability to manage personal workloads effectively, to prioritize tasks, manage timelines, and deliver high-quality results on schedule
• Continuous learning mindset, with a passion for staying up to date with the latest advancements in machine learning and artificial intelligence
• Attention to detail and commitment to producing high-quality, reliable, and maintainable code

Education and skills requirements

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
• Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code
• DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration
• Practical understanding of GPU architecture and cloud compute instances to optimize resource allocation for training and inference workloads
• MLOPS tools: hands on experience with MLflow (or similar tools like weights & biases) for experiment tracking and model registry
• Proven experience working with Large Language Models (LLMs)
• Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns
• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
• Hands-on experience with CI/CD pipelines (GitLab, Jenkins)
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
• Excellent problem-solving and debugging skills, with the ability to identify and resolve issues quickly and effectively
• Relevant work experience in machine learning, data science or a related field

Confidentiality is assured, and only shortlisted candidates will be notified for interviews.