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Job Description

Position : AI Engineer.

Key Responsibilities :


- 4- 6 years of hands-on expertise in AI/ML, Generative AI, and Agentic AI systems for Pune location.


- Design, build, and deploy AI/ML models for classification, prediction, recommendation, and optimization.

- Build and deploy REST APIs for ML/AI models using frameworks such as Flask or FastAPI.

- Apply asynchronous programming and high-performance API design.

- Work with Generative AI frameworks (LLMs, Diffusion models, Transformers, etc.) to develop next-gen AI solutions.

- Build and orchestrate Agentic AI systems capable of reasoning, planning, and executing tasks autonomously.

- Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases.

- Manage model versioning, monitoring, and scaling for APIs in production environments.

- Implement API authentication and security (JWT, OAuth, etc.)

- Integrate AI models with APIs, databases, and enterprise systems for end-to-end workflows.

- Evaluate model performance, scalability, and reliability, ensuring alignment with business goals.

- Research, prototype, and productionize cutting-edge AI techniques.

- Collaborate with product managers, data scientists, and engineers to deliver scalable AI-driven applications.

Required Skills & Experience :

- 4- 6 years of hands-on experience in AI/ML engineering.

- Strong coding skills in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).

- Expertise in Generative AI (LLMs like GPT, LLaMA, Claude, diffusion models, etc.)

- Experience with Agentic AI frameworks (LangChain, LlamaIndex, AutoGPT, CrewAI, or similar).

- Solid understanding of NLP, embeddings, and vector databases (Pinecone, Weaviate, FAISS, Milvus).

- Strong knowledge of the ML lifecycle (data preprocessing, training, evaluation, deployment).

- Expertise in building REST APIs with FastAPI/Flask and integrating them into applications.

- Experience with containerized solutions using Docker & Kubernetes.

- Deployment experience across APIs, containers, and cloud platforms (AWS/GCP/Azure).

- Proficiency in prompt engineering, RAG (Retrieval Augmented Generation), and model fine-tuning.

- Strong problem-solving, debugging, and optimization skills.


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