Job Title

Exp- 3 yrs - 10 yrsMode of Working- WFOCompany Location- Baner, PuneKey Responsibilities1. Problem Identification & Solution DesignUnderstand business problems and design AI-driven automation solutionsArchitect scalable systems combining ML models, LLMs, and rule-based logic2. Data Collection & PreprocessingCollect, clean, and preprocess structured and unstructured dataBuild pipelines for document ingestion, embeddings, and retrieval systems3. Model Development & TrainingDevelop and fine-tune ML, NLP, and Generative AI modelsWork with LLMs and SLMs (Small Language Models) for optimized use casesApply fine-tuning techniques (LoRA, PEFT) for efficient model adaptationImplement embedding models, semantic search, and ranking systems4. RAG & Knowledge SystemsDesign and implement RAG (Retrieval-Augmented Generation) pipelinesWork with vector databases and hybrid retrieval strategiesBuild or integrate knowledge graphs for enhanced reasoning5. Agentic AI & OrchestrationBuild agent-based systems using LangChain, LangGraph, or similar frameworksDesign multi-agent workflows, tool usage, and orchestration pipelinesImplement agent capabilities like memory, planning, and reasoning loops6. Model Evaluation & ValidationEvaluate models using precision, recall, F1-score, and LLM-specific eval methodsReduce hallucinations and improve response quality using prompt and system design7. Deployment & IntegrationBuild and deploy APIs using Flask / FastAPIIntegrate with PostgreSQL and vector databases (FAISS, Pinecone, Chroma, etc.)Deploy on cloud platforms (AWS/GCP/Azure) or on-prem/local environments8. Monitoring & OptimizationMonitor performance (accuracy, latency, cost) and continuously improve systemsOptimize pipelines, prompts, and models for production readiness9. Ethical AI & ComplianceEnsure fairness, bias mitigation, and safe AI practicesImplement guardrails and compliance-aware AI systemsRequired SkillsStrong proficiency in PythonHands-on experience with ML frameworks (PyTorch / TensorFlow)Experience with LLMs, SLMs, embeddings, and RAG pipelinesStrong understanding of fine-tuning techniques (LoRA, PEFT)Experience with LangChain, LangGraph, or agent orchestration frameworksHands-on experience with Flask / FastAPI APIsStrong knowledge of PostgreSQL and vector databasesExperience building automation systems / decision engines / rule-based systemsGood to HaveExperience with MLOps practices and tools (CI/CD for ML, model versioning, monitoring)Familiarity with knowledge graphs (Neo4j, etc.)Experience with local/on-prem LLM deployment and optimizationExposure to real-time/event-driven architecturesBackground in fintech / compliance / transaction monitoring systems