AGI Brains

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.