JD for Lead AI/ML Engineer
Job Title: Lead AI/ML Engineer
Job Purpose:
We are seeking a highly experienced Lead AI/ML Engineer to drive the design,
development, and deployment of advanced AI solutions across the organization. The
ideal candidate will have 6–10 years of experience in AI/ML, with strong expertise in
Generative AI, Large Language Models (LLMs), Computer Vision, and AI platform
architecture.
As a Lead AI/ML Engineer, you will define AI strategy, architect scalable AI systems,
and lead a team of engineers and data scientists to build production-ready AI
solutions. You will play a critical role in translating business problems into innovative
AI-driven products, leveraging technologies such as LLMs, Retrieval-Augmented
Generation (RAG), AI agents, and multimodal AI systems.
You will collaborate closely with Product, Engineering, and Data teams to build
intelligent, scalable, and high-performance AI platforms that power next-generation
applications.
Key Responsibilities:
AI Strategy & Technical Leadership
- Lead the architecture, design, and implementation of enterprise-scale AI/ML
solutions.
- Define and drive the AI/ML roadmap, ensuring alignment with business objectives
and product strategy.
- Provide technical leadership and mentorship to AI/ML engineers and data scientists.
- Establish best practices for AI model development, experimentation, deployment,
and monitoring.
Generative AI & LLM Systems
- Design and develop Generative AI applications using LLMs such as GPT, LLaMA,
Gemini, or custom models.
- Architect and implement Retrieval-Augmented Generation (RAG) pipelines for
enterprise knowledge systems.
- Lead initiatives for LLM fine-tuning, prompt engineering, and model optimization.
- Design AI agent architectures using frameworks like LangChain, LangGraph, and
LlamaIndex.
AI/ML Model Development:
- Develop and deploy NLP, Computer Vision, and multimodal AI models for real-world
business applications.
- Implement advanced deep learning architectures using PyTorch, TensorFlow, or
Keras.
- Identify and evaluate pre-trained and foundation models suitable for specific use
cases.
- Drive data preprocessing, feature engineering, and dataset curation for model
training.
AI Platform & InfrastructureDesign scalable AI infrastructure and MLOps pipelines for model training,
deployment, and monitoring.
- Deploy AI solutions across cloud platforms (AWS, Azure, GCP) or hybrid/on-premise
environments.
- Build APIs, microservices, and pipelines to integrate AI capabilities into enterprise
applications.
- Lead efforts in model optimization, inference acceleration, and resource efficiency.
Performance Optimization & Quality
- Conduct model evaluation, benchmarking, and continuous performance optimization.
- Optimize AI systems for latency, scalability, and cost efficiency.
- Implement testing, monitoring, and observability frameworks for AI systems in
production.
Collaboration & Innovation
- Work closely with Product, Engineering, and Data teams to define AI-powered
product features.
- Stay at the forefront of AI research and emerging technologies, evaluating their
business impact.
- Promote a culture of experimentation, innovation, and knowledge sharing within the
AI team.Required Skills & Experience
AI & Machine Learning
- 6–10 years of experience in AI/ML development and deployment.
- Strong expertise in supervised and unsupervised learning techniques, including
regression, classification, clustering, SVMs, and neural networks.
Generative AI & LLMs
- Hands-on experience with LLM training, fine-tuning, prompt engineering, and
optimization.
- Experience building GenAI applications such as chatbots, AI assistants, and
document intelligence systems.
NLP & Computer Vision
- Strong experience in Natural Language Processing and Computer Vision.
- Hands-on expertise with Transformers, OpenCV, YOLO, and R-CNN architecture.
AI Agents & Frameworks
- Experience with multi-agent frameworks such as LangChain, LangGraph, and
LlamaIndex.
Deep Learning Frameworks
- Proficiency in PyTorch, TensorFlow, or Keras.
Programming
- Strong programming skills in Python with experience in API development and
microservices.
Cloud & AI Infrastructure
- Experience deploying AI models on AWS, Azure, or Google Cloud Platform.
- Familiarity with MLOps pipelines, model serving, and AI lifecycle management.
Vector Databases
- Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or
Weaviate.
Performance Optimization
- Experience optimizing LLM inference for speed, cost, and memory efficiency.
Leadership & CollaborationProven ability to lead AI projects and mentor engineering teams.
- Strong communication skills with the ability to translate business requirements into
AI solutions.
Good to Have
- Experience with multimodal AI (text, image, video, speech).
- Familiarity with Docker, Kubernetes, and containerized AI deployment.
- Experience with model serving frameworks such as FastAPI, Flask, or NVIDIA Triton.
- Exposure to distributed training and large-scale model training pipelines.
Qualifications:
ME (IT, Computer), BE (IT, Computer), MCA, MSC-IT, BCARequired Competencies
- Must possess excellent communication skills – oral and written
- Must possess knowledge of latest technology trends
- Must be a keen learner – should be able to drive “Self Learning”
- Must practice principle of “First Time Right”
- Must have an Eye for Details
- Must have high Customer Orientation
- Must be adaptable to working in multiple / matrix work environment
- Must possess good systems thinking
- Must possess good negotiation, analytical and interpersonal skills. Good leadership &
team player qualities.
- High on personal integrity with ability to establish relationships and work in teams and
should be able to influence stakeholders. Should poses independence, robust ethics and
resilience.
Pay: ₹1,500,000.00 - ₹2,500,000.00 per year
Work Location: In person
