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
EA License No: 11C4879 / Registration ID : R1218583
Apar Technologies Pte Ltd, Singapore
