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Lead AI/ML Engineer
Lead AI/ML Engineer

Lead AI/ML Engineer at Antino · Gurugram · 4 - 6 years · ₹20L - ₹50L / yr · Profitable · Posted 25 Sep 2026

Antino's logo

Lead AI/ML Engineer

anju kushwaha's profile picture
Posted by anju kushwaha
4 - 6 yrs
₹20L - ₹50L / yr
Gurugram
Skills
Generative AI (GenAI)
MLOps
Large Language Models (LLM)
skill iconData Science
PyTorch
skill iconMachine Learning (ML)
Retrieval Augmented Generation (RAG)

Job Description:

We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the

AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.


Machine Learning & LLM Capability:

 End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.

 Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.

 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 LangChain or LlamaIndex.

 Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.

 Project Ownership & Execution

 Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.

 Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.

 Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.

 Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.

 System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.

 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.

 High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.

 Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.

 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 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, or Azure).

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About Antino

Founded :
2018
Type :
Services
Size :
100-1000
Stage :
Profitable

About

Antino is an India-based digital marketing company that offers services such as UI/UX designing, website and mobile application development for businesses.

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We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.

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  • Experience with AI/ML model monitoring, evaluation, and optimization.

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Keywords

AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI

 

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AI & Machine Learning Development 

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  • Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks. 
  • Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions. 
  • Optimize model performance, scalability, latency, and cost. 

Software Engineering & Solution Development 

  • Develop production-grade AI applications using Python and modern software engineering practices. 
  • Build APIs, microservices, and AI-powered enterprise applications. 
  • Integrate AI services with enterprise systems, business applications, and data platforms. 
  • Apply coding standards, automated testing, CI/CD, and version control best practices. 

MLOps & AI Operations 

  • Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management. 
  • Automate model training, validation, testing, and deployment processes. 
  • Monitor model performance, data drift, hallucinations, and operational metrics. 
  • Support continuous improvement and reliability of AI platforms. 

Cloud & Platform Engineering 

  • Develop AI solutions on Azure, AWS, or Google Cloud platforms. 
  • Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies. 
  • Build scalable architectures supporting enterprise AI workloads and real-time inference. 

AI Governance & Security 

  • Ensure compliance with Responsible AI, security, privacy, and regulatory requirements. 
  • Implement model governance, explainability, bias mitigation, and risk management practices. 
  • Maintain standards for secure design, deployment, and operation of AI solutions. 




Required Qualifications 

Education 

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field. 

Experience 

  • 5+ years of software engineering or machine learning development experience. 
  • 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments. 

Technical Skills 

Programming & Engineering 

  • Strong expertise in Python. 
  • Experience with Java, ReactJS, JavaScript, or similar programming languages. 
  • Solid understanding of algorithms, data structures, APIs, and software design principles. 

Artificial Intelligence & Machine Learning 

  • Machine Learning and Deep Learning concepts and frameworks. 
  • Model training, evaluation, optimization, and deployment. 

Generative AI 

  • Large Language Models (LLMs) & SLMs 
  • Prompt Engineering 
  • Retrieval-Augmented Generation (RAG) 
  • AI Agents and Agentic Workflows 
  • Fine-tuning and model customization 
  • Vector embeddings and semantic search 

Frameworks & Tools 

  • PyTorch, TensorFlow, Scikit-learn 
  • LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and Transformers 
  • FastAPI, Flask 

Data & Analytics 

  • SQL and NoSQL databases 
  • Data pipelines, ETL, and data modeling 
  • Experience with AWS, Azure and Google 

MLOps & DevOps 

  • MLflow, Kubeflow, Azure ML, SageMaker 
  • Docker and Kubernetes 
  • Git, GitHub, Azure DevOps, Jenkins 
  • CI/CD automation and model monitoring 

Cloud Platforms 

  • AWS (preferred) 
  • AWS Bedrock or Azure OpenAI Service 
  • AWS SageMaker 
  • Google Vertex AI 

Preferred Qualifications 

  • Experience designing enterprise-scale AI platforms and products.  
  • Knowledge of multi-agent architectures and autonomous AI systems.  
  • Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.  
  • Understanding of AI governance, compliance, and Responsible AI frameworks.  
  • Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.
Read more
GYTWorkz Technologies Pvt Ltd
Hyderabad
5 - 10 yrs
₹10L - ₹40L / yr
Retrieval Augmented Generation (RAG)
LLM Evaluation Frameworks
Model Context Protocol (MCP)
Large Language Models (LLM) tuning
Fine-tuning LLMs
+6 more

Design and develop Agentic AI systems using LLMs, tools, memory,

workflows, and MCP.

Build production-grade RAG pipelines, including ingestion, chunking,

embeddings, retrieval, reranking, and evaluation.

Implement context engineering strategies for improving LLM accuracy,

relevance, and reliability.

Develop and integrate MCP-based tools and services for AI agents.

Work with LLMs, SLMs, quantized models, and model optimization

techniques for efficient inference.

Develop scalable backend services and APIs for AI applications.

Design databases and data models supporting AI/agentic applications.

Implement AI observability covering latency, token usage, cost, failures,

quality, and agent/tool execution.

Apply AI governance and responsible AI practices, including security,

access control, data privacy, and auditability.

Optimize AI systems for latency, scalability, cost, and reliability.

Collaborate with engineering and product teams to take AI solutions from

POC to production.

Strong hands-on experience with GenAI, LLMs, and Agentic AI.

Experience building RAG applications.

Strong understanding of Context Engineering and prompt/context

optimization.

Role Overview

We are looking for a hands-on AI/ML Engineer to design, develop, and deploy

production-ready GenAI and Agentic AI applications. The role involves building

intelligent agents, RAG pipelines, AI APIs, backend services, and scalable AI

infrastructure with a strong focus on context engineering, observability,

governance, and model optimisation.

Key Responsibilities

Required Skills

Practical experience with MCP (Model Context Protocol).

Experience with frameworks such as LangChain, LangGraph,

LlamaIndex, or equivalent.

Knowledge of LLM/SLM deployment and quantization techniques.

Strong Python backend development experience.

Experience developing REST APIs using FastAPI/Flask or equivalent.

Strong understanding of SQL/NoSQL databases and database design.

Experience with vector databases such as Qdrant, Pinecone, Weaviate,

ChromaDB, or FAISS.

Understanding of AI observability, evaluation, monitoring, and

governance.

Experience with cloud platforms and production deployment is preferred.

Strong understanding of software engineering principles, Git, testing, and

CI/CD.

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Service Co
Service Co
Agency job
via Vikash Technologies by Rishika Teja
Pune, Mumbai
5 - 10 yrs
₹15L - ₹40L / yr
Artificial Intelligence (AI)
Generative AI
Large Language Models (LLM)
Retrieval Augmented Generation (RAG)

Hiring for AI Engineer


Exp: 5 - 10 yrs

Edu : BE/B.Tech/MCA

Work Location : Pune / Mumbai


Skill Set:


Total experience ranging from 5–10 years in software engineering/AI roles

Min 5 years strong programming experience in Python is a MUST

Min 3.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks

2+ years shipping LLM systems in production

Experience with cloud platforms (AWS/Azure/GCP)

Read more
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