Senior AI Engineer

VMO ALTEN SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

A technology consultancy firm in Singapore is seeking a Senior AI Engineer to join their growing engineering team. The role involves building advanced AI solutions, collaborating closely with business stakeholders, and ensuring deployment and monitoring of ML models using MLOps best practices. Candidates should have at least 8 years of relevant experience and strong expertise in Python, AI/ML, and data science tools. The ideal candidate will thrive in a collaborative environment and demonstrate excellent communication skills.

Qualifications

• 8+ years of experience in software development, data science, and ML, with at least 3+ years in AI engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Knowledge of data privacy, anonymization, and compliance in regulated industries.

Responsibilities

• Build and maintain data pipelines and ensure model performance.
• Collaborate with business stakeholders to define AI solutions.
• Automate model retraining and ensure consistent performance.

Skills

Python programming

AI/ML knowledge

MLOps tools

CI/CD pipelines

Data science techniques

Communication with stakeholders

Education

Degree or master's in AI/ML and data science

Tools

TensorFlow

PyTorch

MLflow

Airflow

Docker

Kubernetes

Job description

Overview

Senior AI Engineer role description with responsibilities and required qualifications.

Responsibilities

• As a Senior AI Engineer, you’ll be part of growing engineering team and help to build the next generation AI Solutions.
• Collaborate with business stakeholders to understand use cases and define AI solution; work on Proof of Concepts wherever needed
• Engineer and deploy ML models into production using MLOps best practices (model versioning, monitoring, CI/CD, etc.).
• Build & maintain data pipelines and model performance for scalability and maintainability.
• Ensure all models adhere to organizational AI policies, responsible AI practices, and audit requirements.
• Support data exploration, feature engineering, and occasional model building where needed.
• Automate model retraining, testing, and monitoring to ensure performance over time.
• Document ML workflows, governance checkpoints, and risk assessments.
• Partner with CloudOps, DevOps, IT, and security teams to integrate solutions into enterprise platforms.
• The position requires autonomy and reliability in performing duties while maintaining close communication with rest of stake-holders.

Qualifications and Profile

Mandatory:

• Have degree or master’s degree in the field of AI / ML and data science with proven ability to design and develop models
• 8+ years of experience in software development, data science and ML, with at least 3+ years in AI engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong programming skills in Python with Solid knowledge of AI/ML, including LLMs and data science libraries like pandas, scikit-learn, TensorFlow/PyTorch, etc.
• Experience with LLM Orchestration frameworks like Langchain, LangGraph, vLLM, LMDeploy.
• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
• Experience with MLOps tools: MLflow, Airflow, Kubeflow, or similar.
• Familiarity with either of cloud platforms (GCP, AWS) for AI Solutioning and ML deployment.
• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred skills

• Experience with Responsible AI frameworks and bias/fairness testing.
• Exposure to feature stores, model registries, and data versioning.
• Knowledge of data privacy, anonymization, and compliance in regulated industries (e.g., banking, healthcare).

Other Professional Skills and Mind-set

• Ability and willingness to learn and adopt new technologies
• Strong organizational and communication skills
• Strong analytical and problem solving skills
• Awareness of various software development procedures
• Ability to follow defined procedures
• Understanding and respect of cultural diversity