AI/ML Engineer

Role Purpose

We are looking for an AI/ML Engineer to design, develop, deploy and maintain intelligent capabilities across CHRP-INDIA Products and our wider digital product ecosystem. The objective is to progressively build an intelligent enterprise platform capable of learning from organizational data, identifying capability gaps and recommending appropriate interventions.

Key Responsibilities

1. Productionize machine-learning models developed by Data Scientists.
2. Design ML inference services and APIs.
3. Develop recommendation engines.
4. Build adaptive algorithms.
5. Develop AI-assisted mapping algorithms.
6. Implement NLP capabilities for user interaction.
7. Develop semantic search and retrieval systems.
8. Build enterprise knowledge retrieval and RAG solutions where appropriate.
9. Develop LLM-powered enterprise assistants.
10. Implement vector databases and embeddings.
11. Develop skill/role/content matching algorithms.
12. Implement model monitoring and versioning.
13. Build automated ML pipelines.
14. Integrate AI services with .NET backend applications through APIs.
15. Implement secure enterprise AI architecture.
16. Develop mechanisms for human review and feedback.
17. Design AI systems with traceability and explainability appropriate to HR/workforce use cases.
18. Implement safeguards against inappropriate automated decisions.
19. Optimize inference cost and performance.
20. Support cloud and private/on-premises AI deployment architectures where required.

Target Product Capabilities

The AI/ML Engineer will help develop:

• Intelligent Skill Engine
• Personalized Learning Engine
• Competency Intelligence Engine
• Workforce Intelligence Assistant
• Content Intelligence
• Predictive Intervention Engine

Required Skills

• 3–5 years in ML/AI engineering or related software engineering.
• Python.
• Machine-learning frameworks.
• REST APIs / microservices.
• SQL.
• Model deployment.
• Docker.
• Cloud ML architecture.
• MLOps fundamentals.
• NLP.
• Embeddings/vector search.
• LLM application development.
• Git and CI/CD.

Preferred Skills

Azure AI/Azure ML or equivalent, MLflow, PyTorch/TensorFlow, LangChain/LlamaIndex or equivalent orchestration frameworks, Vector databases, RAG, Knowledge Graphs, Recommendation Systems, Kubernetes, Enterprise AI security.

Key Deliverables

Production ML Services, Recommendation Engine, Adaptive Learning Engine, AI APIs, RAG/Knowledge Systems, Model Deployment Pipelines, Monitoring Framework, AI Integration Architecture