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Lead AI/ML Engineer

SRV Jansampark Kendra

Vadodara

6-10 years

Today

$18.1K–30.1K/yr

Full-time

Onsite

Skills Required

LLM

RAG

Gen AI

LangChain

LlamaIndex

Gemini

GPT

Transformers multimodal AI

LangGraph

LLaMA

NLP

Computer Vision

PyTorch

TensorFlow

Description

Enterprise AI/ML leadership role focused on building and scaling GenAI, LLM, NLP, and computer vision solutions. The position combines technical architecture, model development, MLOps, and cross-functional collaboration.

Company: Starvoke (SRV JanSampark Kendra)

Role: AI/ML Lead

Location: In person

Experience

- 6–10 years of experience in AI/ML development and deployment

- Strong expertise in supervised and unsupervised learning techniques

- 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

- Strong experience in Natural Language Processing and Computer Vision

- Hands-on expertise with Transformers, OpenCV, YOLO, and R-CNN architecture

- Experience with multi-agent frameworks such as LangChain, LangGraph, and LlamaIndex

- Proficiency in PyTorch, TensorFlow, or Keras

- Strong programming skills in Python with experience in API development and microservices

- Experience deploying AI models on AWS, Azure, or Google Cloud Platform

- Familiarity with MLOps pipelines, model serving, and AI lifecycle management

- Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate

- Experience optimizing LLM inference for speed, cost, and memory efficiency

- Proven ability to lead AI projects and mentor engineering teams

- Strong communication skills with the ability to translate business requirements into AI solutions

Qualification

- ME (IT, Computer)

- BE (IT, Computer)

- MCA

- MSC-IT

- BCA

Responsibilities

- Lead the architecture, design, and implementation of enterprise-scale AI/ML solutions

- Define and drive the AI/ML roadmap aligned with business objectives and product strategy

- Provide technical leadership and mentorship to AI/ML engineers and data scientists

- Establish best practices for model development,



experimentation, deployment, and monitoring

- Design and develop Generative AI applications using LLMs or custom models

- Architect and implement Retrieval-Augmented Generation pipelines for enterprise knowledge systems

- Lead initiatives for LLM fine-tuning, prompt engineering, and model optimization

- Design AI agent architectures using LangChain, LangGraph, and LlamaIndex

- Develop and deploy NLP, Computer Vision, and multimodal AI models for business applications

- Implement advanced deep learning architectures using PyTorch, TensorFlow, or Keras

- Identify and evaluate pre-trained and foundation models for specific use cases

- Drive data preprocessing, feature engineering, and dataset curation for model training

- Design scalable AI infrastructure and MLOps pipelines for training, deployment, and monitoring

- Deploy AI solutions across cloud 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

- 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

- Work closely with Product, Engineering, and Data teams to define AI-powered product features

- Evaluate emerging AI research and technologies for business impact

- Promote a culture of experimentation, innovation, and knowledge sharing within the AI team

Additional Responsibilities

- Supervise and guide supervised and unsupervised learning use cases such as regression, classification, clustering, and SVMs

- Support model training and deployment for real-world business applications





- Work in multiple / matrix work environment

- Practice first-time-right delivery mindset

- Maintain eye for details

- Demonstrate customer orientation

- Use systems thinking

- Apply negotiation, analytical, and interpersonal skills

- Show leadership and team player qualities

- Maintain personal integrity, robustness of ethics, resilience, and stakeholder influence

Nice To Have

- Experience with multimodal AI covering text, image, video, and 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

More Skills

AI/ML, prompt engineering, model optimization, Keras, Python, APIs, microservices, AWS, Azure, Google Cloud Platform, MLOps, model serving, AI lifecycle management, FAISS, Pinecone, ChromaDB, Weaviate, OpenCV, YOLO, R-CNN, Docker, Kubernetes, FastAPI, Flask, NVIDIA Triton, distributed training

Other

- Pay: ₹1,500,000.00 - ₹2,500,000.00 per year

- Starvoke (SRV JanSampark Kendra) never charges for job vacancies

- Excellent oral and written communication expected

- Knowledge of latest technology trends expected

- Robust self-learning mindset expected

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

Generative AI with Large Language Models

Coursera

Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

Functions, Tools and Agents with LangChain

Coursera

Advanced LangChain covering function calling, tool use, and conversational agents.

Introduction to Generative AI

Coursera

Google Cloud introduction covering Gen AI concepts, model types, and Google AI tools.

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