• Collaborate with data scientists and business stakeholders to understand use cases and define ML 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 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 Master's degree in the field of AI / ML and data science with proven ability to design and develop models
• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, etc.).
• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
• Experience with MLOps tools: MLflow, TFX, Airflow, Kubeflow, or similar.
• Familiarity with cloud platforms (GCP, AWS, or Azure) for 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

Interested candidates kindly submit your updated CV in Word Format to: Jasmin@Tangspac.com. Only shortlisted candidates will be notify. Thank you.