Machine Learning Engineer

2 weeks ago

Singapur, Singapore TANGSPAC CONSULTING PTE LTD Full time

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: Only shortlisted candidates will be notify. Thank you.

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