We are seeking a passionate and hands-on Applied AI Builder to join our team and drive innovation at the intersection of Generative AI, Machine Learning, and Cloud technologies. This role is ideal for someone with a strong foundation in ML / AI, practical experience with LLMs and GenAI frameworks, and a desire to solve real-world problems using cutting-edge tools and techniques.
As an Applied AI Builder, youll work on designing, developing, and deploying AI solutions across multiple domains, leveraging state-of-the-art models and frameworks. You will collaborate with cross-functional teams to build scalable applications that integrate GenAI, RAG (Retrieval-Augmented Generation), and vector-based search.
Key Responsibilities :
- Design and develop AI / GenAI applications using LLMs and frameworks like LangChain, Haystack, etc.
- Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search techniques.
- Build, fine-tune, and deploy ML and DL models using PyTorch, TensorFlow, or JAX.
- Develop robust, production-ready code in Python with reusable and scalable modules.
- Optimize and deploy models on cloud platforms such as AWS, GCP, or Azure.
- Collaborate with data engineers, product managers, and designers to deliver AI-driven features and services.
- Stay current with the latest research and advancements in GenAI, LLMs, and emerging ML technologies.
Required Skills & Experience :
3+ years of hands-on experience in Machine Learning, Deep Learning, and Python programming.Strong exposure to Generative AI and working with Large Language Models (LLMs).Experience with Prompt Engineering, LangChain, or Haystack.Proficiency with vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus).Solid understanding of RAG-based architectures and semantic search.Familiarity with cloud platforms (AWS, GCP, or Azure) and deploying AI models at scale.Experience with at least one deep learning framework : PyTorch, TensorFlow, or JAX.Good to Have :
Experience building AI-based chatbots or intelligent agents.Knowledge of model optimization techniques (quantization, pruning, distillation).Exposure to MLOps tools and workflows for scalable AI deployment.Published work, open-source contributions, or participation in AI competitions (e.g., Kaggle, Hugging Face).Why Join Us?
Work at the forefront of AI and Generative AI innovation.Build impactful, production-grade solutions that are deployed and used at scale.Collaborate with a highly skilled, passionate team in a fast-paced and agile environment.Opportunity for rapid growth and working on real-world AI applications across industries.(ref : hirist.tech)