AI/Ml Engineer

2 weeks ago

Pune, Maharashtra, India AGI Brains Full time ₹ 8,00,000 - ₹ 12,00,000 per year

About the Role:

We are seeking an enthusiastic AI/ML Engineer to join our team, with strong skills in Python, Generative AI frameworks, and scalable cloud deployment. You will work on cutting-edge LLMs and open-source AI models, fine-tune them for business applications, and deploy them seamlessly on AWS and containerized environments.

This role is suited for freshers with strong project work as well as early-career professionals looking to grow in LLM development, MLOps, and enterprise AI deployments.

Key Responsibilities:

  • Develop and deploy scalable APIs/microservices using Flask and FastAPI.
  • Work with state-of-the-art LLMs (Gemini, GPT-4/4o, LLaMA 3, Mistral, Mixtral, Falcon, Claude) and integrate them into real-world applications.
  • Fine-tune and optimize open-source LLMs (LLaMA, Mistral, Falcon, etc.) for on-premise enterprise use cases.
  • Implement RAG (Retrieval Augmented Generation) workflows using LangChain, LangGraph, and vector databases.
  • Design and manage containerized and serverless deployments on AWS (EC2, S3, ECR, Lambda, API Gateway) using Docker.
  • Collaborate with cross-functional teams to integrate AI services into production systems.
  • Ensure performance, scalability, and cost optimization of deployed AI solutions.
  • Stay ahead of trends in Generative AI, multi-modal models, and AI infrastructure.

Required Skills:

  • Strong programming foundation in Python.
  • Experience building APIs using Flask and FastAPI.
  • Knowledge of LLM frameworks: Hugging Face Transformers, LangChain, LangGraph.
  • Familiarity with leading models: Google Gemini, OpenAI GPT series, Meta LLaMA, Mistral/Mixtral, Falcon, Claude.
  • Cloud expertise with AWS services (EC2, S3, ECR, Lambda, API Gateway).
  • Containerization with Docker and version control using Git/GitHub.
  • Experience with Elasticsearch for indexing, search, and RAG use cases.

Nice to Have (Added Advantage):

  • Experience fine-tuning open-source LLMs (LLaMA, Mistral, Falcon, etc.) for on-prem deployments.
  • Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus).
  • Understanding of MLOps tools (MLflow, DVC, SageMaker) for CI/CD in AI.
  • Exposure to multi-modal models (text + image, text + audio) like Gemini Pro, LLaVA, or OpenAI GPT-4o.
  • Database skills: PostgreSQL, MongoDB, or NoSQL stores.
  • Strong grasp of data structures, algorithms, and system design.

What We Offer:

  • Hands-on experience with cutting-edge AI models in real-world use cases.
  • Opportunity to work on both cloud and on-prem deployments.
  • Fast-paced learning with mentorship in LLM product development & MLOps.

Competitive salary, career growth, and exposure to global AI projects.

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