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Job Description

Job Summary :

We are seeking an AI/ML Developer with 3+ years of experience in building and deploying intelligent systems. The role focuses on developing scalable ML solutions, optimizing models, and solving real-world business problems.

Key Responsibilities :

1. Design, develop, train, evaluate, and deploy ML/DL models

2. Work on classification, regression, clustering, NLP, and recommendation systems

3. Perform data preprocessing, feature engineering, hyperparameter tuning, and model optimization

4. Hands-on experience with AI tools and developer productivity tools such as n8n, Cursor, Claude, ChatGPT, GitHub Copilot, and similar AI-assisted automation/coding platforms

5. Experience using AI tools effectively for automation, development workflows, debugging, code generation, and productivity enhancement

6. Build and fine-tune Generative AI models (LLMs, VAEs, diffusion models) using Hugging Face, LangChain, OpenAI, LlamaIndex

7. Develop RAG pipelines, prompt engineering workflows, and embedding-based search systems

8. Build Multi-Agent Systems and agent workflows using CrewAI, LangGraph, AutoGen, etc.

9. Integrate AI solutions into scalable production systems

10. Monitor model performance, accuracy, latency, and reliability

11. Collaborate with cross-functional teams and stay updated with latest AI/ML advancements.

Requirements :

1. Strong Python programming skills

2. Strong understanding of ML concepts :

3. Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or Keras

4. Practical experience in :

i. Model training & fine-tuning

ii. LLMs & Generative AI

iii. RAG architecture

iv. Prompt Engineering

v. Embeddings & Vector Search

5. Experience with vector DBs : Pinecone, Weaviate, Chroma, FAISS

6. Experience with LangChain, LlamaIndex, OpenAI APIs

7. Knowledge of Multi-Agent/Agentic AI systems

8. Experience with FastAPI/Flask model deployment

9. Familiarity with AWS/GCP/Azure

10. Knowledge of Git and MLOps tools (MLflow, Airflow, Kubeflow)

11. Basic understanding of Spark/Hadoop and ETL pipelines

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