Vacancy description
HuntingCube
भारत
About the Role : We are looking for a Machine Learning Engineer to build and deploy production-grade AI systems powered by Large Language Models (LLMs). In this role, you will work on retrieval-augmented generation (RAG), search, multilingual NLP, document understanding, evaluation frameworks, and AI-powered workflows. You will collaborate closely with research, engineering, and product teams to deliver reliable, scalable AI solutions used in real-world https://jobeax.com/link/D97KR0fNczjlIZqw Responsibilities : - Design, build, and deploy production-ready LLM and NLP applications.- Develop retrieval and search pipelines using RAG, embeddings, vector databases, and reranking techniques.- Build AI agents and workflow automation for complex business use cases.- Fine-tune and adapt open-source LLMs using techniques such as LoRA, QLoRA, or PEFT.- Develop multilingual NLP solutions including summarization, translation, information extraction, and question answering.- Design evaluation frameworks to measure model quality, hallucinations, factuality, latency, and overall user experience.- Build feedback pipelines that capture production failures and improve model performance.- Work closely with data, engineering, and product teams to translate business requirements into scalable ML solutions.- Deploy and maintain ML models in production while ensuring scalability, monitoring, and reliability.- Continuously improve system performance, inference efficiency, and operational https://jobeax.com/link/hGtX6zTSf2DC9SxB Skills : - 3-6 years of experience building production Machine Learning or NLP systems.- Strong programming skills in Python.- Hands-on experience with PyTorch and Hugging Face Transformers.- Experience working with Large Language Models (LLMs).- Strong understanding of Retrieval-Augmented Generation (RAG) architectures.- Experience with vector search technologies such as FAISS, Pinecone, Milvus, Chroma, or similar.- Experience with prompt engineering, LLM evaluation, and model fine-tuning.- Familiarity with LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks.- Experience building REST APIs using FastAPI or similar frameworks.- Experience deploying ML solutions using Docker and cloud platforms (AWS, Azure, or GCP).- Good understanding of software engineering best practices, version control, testing, and CI/CD.Preferred Skills : - Experience with AI agents or multi-agent systems.- Experience with multilingual NLP applications.- Experience with recommendation systems or semantic search.- Experience with vLLM, Text Generation Inference (TGI), or LLM serving frameworks.- Familiarity with ML evaluation tools such as Arize Phoenix, LangSmith, or similar.- Experience working with enterprise AI applications in domains such as legal, healthcare, finance, or public sector.- Publications or open-source contributions in AI/ML are a https://jobeax.com/link/sTFvKUrNDmT494Mr to Have : - Experience with distributed training, DeepSpeed, or FSDP.- Experience optimizing inference latency and deployment costs.- Knowledge of model monitoring, observability, and experimentation frameworks.- Familiarity with cloud-native architectures and https://jobeax.com/link/kYTaDF7CEnxzin76 You'll Work On : - Production LLM applications- Retrieval-Augmented Generation (RAG)- AI Agents & Workflow Automation- Search & Recommendation Systems- Multilingual NLP- Evaluation & Observability- Document Intelligence- Prompt Engineering & Fine-tuning- Cloud-native ML DeploymentIf you're passionate about building reliable AI systems that solve real-world problems at scale, we'd love to hear from you. (ref:hirist.tech)