AI/ML Engineer

Role Overview

Focus on AI/ML Model Development, Fine-tuning, Agentic AI, and Generative AI. This role requires a self-starter capable of leading projects and taking end-to-end ownership while working in an Agile environment.

Responsibilities

• Develop, fine-tune, and deploy AI/ML models.
• Implement RAG, embeddings, vector databases, and semantic search.
• Build AI agents, multi-agent workflows, and utilize tool/function calling.
• Manage tasks using Jira for story creation, sprint planning, and bug tracking.
• Participate in Agile/Scrum ceremonies including daily stand-ups and retrospectives.

Requirements

• Strong proficiency in Python and writing production-ready, scalable code.
• Deep understanding of Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI.
• Hands-on experience with PyTorch, TensorFlow, Hugging Face, Scikit-learn, and LangChain/LlamaIndex.
• Experience with LLMs such as OpenAI, Claude, Gemini, and Llama.
• Familiarity with Docker, FastAPI, Kubernetes, MLflow, and cloud platforms like AWS, Azure, or GCP.
• Proficiency with SQL, PostgreSQL, MongoDB, and vector databases like Pinecone, Weaviate, ChromaDB, or Milvus.
• Strong English fluency and ability to collaborate with clients.

Nice to Have

• Experience with Voice AI (Whisper, Deepgram, TTS/STT) and multimodal AI.
• Knowledge of LoRA, PEFT, quantization, MCP, and GPU/inference optimization.

Benefits

• Food provided
• Health insurance
• Life insurance
• Provident Fund

Skills

• Python
• PyTorch
• LangChain
• Generative AI
• AWS