AI/ML Engineer

About the Role

Job Description: We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertiseinGenerativeAI(GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownershipoftheAI lifecycle—from initial architectural design to final production execution. You will leadthedevelopmentof scalable AI\-powered applications, demonstrating exceptional execution skills and theabilitytodeliverhigh\-performance results under pressure in demanding production environments. Machine Learning \& LLM Capability:  End\-to\-End ML Engineering: Build and manage comprehensive ML pipelines, includingdataingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow,and Scikit\-learn.  Advanced LLM Systems: Design and implement sophisticated LLM\-based applicationssuchasautonomous agents, chatbots, and complex automation tools.  Generative AI Specialization: Architect and optimize Retrieval\-AugmentedGeneration(RAG)pipelines using vector databases like FAISS, Pinecone, or Weaviate. 1\) Model Optimization: Fine\-tune open\-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.  Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as 2\)LangChain or LlamaIndex.  Prompt Engineering: Implement expert\-level prompt engineering, tool/function calling, and structured output generation.  Project Ownership \& Execution 3\) Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization. 4\)Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable. 5\) Execution Excellence: Write clean, high\-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution. 6\)Leadership \& Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality. 7\)System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows. 8\)Performance Under Pressure Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real\-time processing. 9\)High\-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements. 10\)Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast\-paced environments. 11\)Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress. Qualifications:  Bachelor’s or Master’s degree in Computer. Qualification:  Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.  Proven expertise in Python, system design, and scalable AI/ML architecture.  Deep knowledge of NLP, Computer Vision, and Deep Learning models.  Hands\-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP,orAzure). Pay: ₹2,000,000\.00 \- ₹4,500,000\.00 per year Benefits: * Cell phone reimbursement * Flexible schedule * Health insurance * Leave encashment * Life insurance * Paid sick time * Provident Fund Work Location: In person