AI ML Developer

Designation: AI/ML Developer

Experience: 3 - 5 Years

Location: Ahmedabad

Priority: Immediate joiners preferred

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

• Design, develop, train, evaluate, and deploy ML/DL models
• Work on classification, regression, clustering, NLP, and recommendation systems
• Perform data preprocessing, feature engineering, hyperparameter tuning, and model optimization
• 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
• Experience using AI tools effectively for automation, development workflows, debugging, code generation, and productivity enhancement
• Build and fine-tune Generative AI models (LLMs, VAEs, diffusion models) using Hugging Face, LangChain, OpenAI, LlamaIndex
• Develop RAG pipelines, prompt engineering workflows, and embedding-based search systems
• Build Multi-Agent Systems and agent workflows using CrewAI, LangGraph, AutoGen, etc.
• Integrate AI solutions into scalable production systems
• Monitor model performance, accuracy, latency, and reliability
• Collaborate with cross-functional teams and stay updated with latest AI/ML advancements
  
  

• Strong Python programming skills
• Strong understanding of ML concepts:
• Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or Keras
• Practical experience in:
• Model training & fine-tuning
• LLMs & Generative AI
• RAG architecture
• Prompt Engineering
• Embeddings & Vector Search
• Experience with vector DBs: Pinecone, Weaviate, Chroma, FAISS
• Experience with LangChain, LlamaIndex, OpenAI APIs
• Knowledge of Multi-Agent/Agentic AI systems
• Experience with FastAPI/Flask model deployment
• Familiarity with AWS/GCP/Azure
• Knowledge of Git and MLOps tools (MLflow, Airflow, Kubeflow)
• Basic understanding of Spark/Hadoop and ETL pipelines
  

• 5-day work week & Flexible work hours
• Growth-focused journey with regular rewards and recognition
• Focus on learning & development
• Competitive, goal-driven culture