
AI/Ml Engineer
2 weeks ago
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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