Senior AI / ML Engineer

YOXIA PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A technology solutions provider in Singapore is seeking an experienced AI Engineer to design and deploy ML and GenAI solutions. Responsibilities include developing scalable AI systems, collaborating with business stakeholders, and implementing MLOps best practices. The ideal candidate will have over 8 years in software development, strong Python and machine learning skills, and experience in AI governance. This role offers the opportunity to work on innovative projects in a dynamic environment.

Qualifications

• 8+ years in software development, data science, and ML, including 3+ years in AI engineering roles.
• Proficient in full ML lifecycle, including deployment, monitoring, and data science techniques.
• Understanding of AI governance and model risk management in regulated industries.

Responsibilities

• Design and deploy end-to-end ML and GenAI solutions.
• Collaborate with stakeholders to develop solutions and create Proof of Concepts.
• Implement MLOps best practices and develop data pipelines.

Skills

Python skills

Machine Learning frameworks knowledge

MLOps tools experience

Strong problem-solving

Data wrangling

Education

Degree or Master's in AI, ML, or Data Science

Tools

TensorFlow

PyTorch

scikit-learn

MLflow

Airflow

Docker

Kubernetes

AWS

GCP

Job description

• Design and deploy end-to-end ML and GenAI solutions using both traditional machine learning and LLM/Agentic technologies.
• Build scalable, production‑grade AI systems while ensuring compliance with AI governance and regulatory standards.
• Collaborate with business stakeholders to define use cases, develop solutions, and create Proof of Concepts.
• Implement MLOps best practices, including model versioning, monitoring, CI/CD, and automated retraining.
• Develop and maintain data pipelines to ensure model performance, scalability, and maintainability.
• Document workflows and risk assessments while supporting responsible AI practices and audit requirements.
• Partner with cross‑functional teams (CloudOps, DevOps, IT, Security) to integrate AI solutions into enterprise platforms.

The Successful Applicant

A successful candidate should have:

• Degree or Master's in AI, ML, or Data Science with proven model development experience
• 8+ years in software development, data science, and ML, including 3+ years in AI engineering roles
• Strong Python skills, knowledge of ML/AI frameworks (TensorFlow, PyTorch, scikit‑learn, pandas) and LLM orchestration (Langchain, LangGraph, vLLM, LMDeploy)
• Experience with NoSQL/Graph databases, MLOps tools (MLflow, Airflow, Kubeflow), CI/CD pipelines, containerization (Docker/Kubernetes), and cloud platforms (AWS/GCP)
• Proficient in full ML lifecycle, including data wrangling, model development, deployment, monitoring, and data science techniques (supervised/unsupervised learning, NLP, time series)
• Governance & Compliance: Understanding of AI governance, model risk management, Responsible AI, bias/fairness testing, and regulatory requirements in regulated industries
• Strong problem‑solving, analytical, communication, and organizational skills, with adaptability, teamwork, and respect for cultural diversity