At H&P, our people are our strength.

We are looking for a passionate AI/ML Developer to 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: 2–5 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!

India: Intern/Trainee (Software Engineer)