AI/ML Engineers

4 hours ago

bangalore, India Prana Tree Full time

Job Title: AI/ML Engineer Experience: 4 – 6 Years Work Mode: Work from Office (WFO) Locations: Chennai | Bangalore | Hyderabad Position Overview We are seeking a highly skilled AI/ML Engineer responsible for designing, developing, and deploying scalable Machine Learning and Generative AI solutions. The ideal candidate will have strong expertise in data engineering, model lifecycle management, and modern AI frameworks — with a focus on production-grade AI/ML systems and automation through MLOps and LangOps practices. Key Responsibility AI/ML Development Design, train, and optimize machine learning models for real-world enterprise applications. Build and maintain end-to-end ML pipelines , including data pre-processing, feature engineering, model training, validation, and deployment. Collaborate with data engineers and software developers to integrate ML models into production systems. Monitor and maintain model performance , detect data drifts, and implement retraining strategies for continuous improvement. Generative AI (GenAI) Agentic Solution Design & Orchestration Architect LLM-powered applications with dynamic intent routing and tool integration. Develop agentic workflows using frameworks such as LangGraph or equivalents to ensure determinism, scalability, and guardrails. Integrate MCP-compatible tools and services to extend GenAI capabilities. Retrieval & Embeddings Build and optimize RAG (Retrieval-Augmented Generation) systems using advanced embedding, chunking, and reranking strategies. Enhance search efficiency through vector store optimization , hybrid search, and metadata schema design. Prompting & Model Strategy Design robust prompting frameworks and function-calling templates. Evaluate generic vs. fine-tuned LLMs based on cost, latency, accuracy, and maintainability. Data & Integrations Implement NL2SQL and guarded SQL execution patterns. Connect models with microservices and enterprise APIs for secure, real-time data access. Define and maintain data schemas, metadata, and lineage for reliability and traceability. Production Readiness Establish evaluation datasets and automated regression tests for RAG and agentic solutions. Monitor performance metrics — precision, recall, hallucination rate, latency, and cost. Enforce data privacy, PII protection, and access control across deployments. MLOps / LangOps Manage versioning of prompts, models, and embeddings , and oversee controlled rollouts with A/B testing. Implement monitoring, tracing, and telemetry for AI agents and tool invocations. Define fallback, timeout, and retry policies to ensure system reliability and resiliency. Qualifications Programming: Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Frameworks: Hands-on experience with TensorFlow or PyTorch . Machine Learning & Deep Learning: Experience with supervised, unsupervised, and reinforcement learning methods. Data Management: Proficient with SQL/NoSQL databases , data preprocessing, and feature engineering. MLOps: Exposure to CI/CD , pipeline automation, and model deployment workflows. Preferred Skills Experience with LangChain , LangGraph , or other agentic AI frameworks. Familiarity with vector databases and semantic search . Exposure to cloud-based ML platforms such as AWS, Azure, or GCP . Excellent problem-solving, communication, and collaboration skills.

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    6 hours ago

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