Senior AI/ML Engineer

KRIS INFOTECH PTE. LTD.; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A technology company based in Singapore is seeking an experienced AI Engineer to build and deploy next-generation AI solutions. This role requires expertise in the end-to-end ML lifecycle, strong programming skills in Python, and proficiency with MLOps tools. Candidates should have at least 8 years of experience in software development and a degree in AI, ML, or data science. You will collaborate with various stakeholders and ensure compliance with AI governance and regulatory requirements.

Qualifications

• 8+ years of experience in software development, data science, and ML.
• Proven end-to-end ML lifecycle experience.
• Familiarity with cloud platforms for ML deployment.

Responsibilities

• Build AI solutions and collaborate with stakeholders.
• Deploy ML models using MLOps best practices.
• Automate model retraining and ensure compliance.

Skills

Python programming

AI/ML knowledge

Data science libraries

MLOps tools

NoSQL databases

CI/CD and containerization

Communication skills

Problem-solving

Education

Degree or Master’s in AI/ML/Data Science

Tools

TensorFlow

PyTorch

Kubeflow

Docker

Kubernetes

Job description

Job Description

• 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.

Requirements

• 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.