At H&P, our people are our strength.
Job Description: AI/ML Intern
Location: Goa/Noida
Experience: 0–2 years
Department: AI/ML Engineering
About the Role
We are looking for a passionate AI/ML Internto join our team and contribute to building next-generation AI applications. You will work on machine learning models, Generative AI systems, RAG (Retrieval-Augmented Generation) pipelines, and Agentic AI frameworks, leveraging cloud platforms such as Azure AI (or similar) to develop scalable, production-ready solutions.
This role is ideal for someone who has hands-on experience in Python, AI/ML frameworks, and modern GenAI techniques and is excited about applying them to solve real-world business problems.
Key Responsibilities
- Design, build, and deploy AI/ML models for classification, prediction, and optimization tasks.
- Develop and implement GenAI solutions (LLMs, prompt engineering, fine-tuning, embeddings).
- Build RAG pipelines integrating vector databases, knowledge graphs, and LLMs.
- Implement Agentic AI workflows for automation, reasoning, and multi-step task execution.
- Work with Azure AI services (OpenAI, Cognitive Search, ML Studio, Data Factory) or similar platforms (AWS Sagemaker, GCP Vertex AI).
- Optimize ML pipelines for scalability, performance, and cost efficiency in cloud and edge environments.
- Collaborate with cross-functional teams (data engineers, domain experts, product managers).
- Stay updated with the latest AI/ML/GenAI research and tools and integrate best practices.
Required Skills & Qualifications
- Education: B.E./B.Tech/M.Tech in Computer Science, AI/ML, Data Science, or related field.
- Experience: 0–2 years in AI/ML development.
- Programming: Strong in Python (NumPy, Pandas, PyTorch/TensorFlow, LangChain, Transformers).
- ML/AI: Model training, fine-tuning, evaluation, deployment.
- GenAI: Experience with LLMs (OpenAI, LLaMA, Mistral, etc.), embeddings, and prompt design.
- RAG Systems: Knowledge of vector databases (Pinecone, FAISS, Weaviate, Milvus).
- Agentic AI: Familiarity with AI agents (LangChain Agents, AutoGen, CrewAI, Semantic Kernel).
- Cloud: Hands-on with Azure AI (preferred) or AWS/GCP AI services.
- MLOps: Model versioning, CI/CD, deployment using MLflow/Docker/Kubernetes.
- Strong problem-solving, analytical, and debugging skills.
Good to Have
- Knowledge of NLP, Computer Vision, or Multi-modal AI.
- Experience with knowledge graphs or graph databases.
- Exposure to edge AI deployments.
- Contributions to open-source AI/ML projects.
Thank you for your interest in joining our team!
