Artificial Intelligence Engineer

Hack And Grow Consultancy; Gurugram District; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Hack And Grow Consultancy is seeking an AI/ML Engineer to design, build, and deploy end-to-end ML/AI models. You will develop Generative AI applications using LLMs, RAG pipelines, and fine-tuning, and build scalable data pipelines integrated with core product APIs.

The role requires 3+ years of AI/ML experience with Generative AI focus, strong Python/SQL, and hands-on work with PyTorch/TensorFlow, Hugging Face, LangChain, and vector databases.

Qualifications

• Education: B.E./B.Tech./M.Tech./MS in CS/DS/AI or related field.
• Minimum 3 years as AI/ML Engineer with focus on Generative AI/LLMs.
• Strong production-grade Python/SQL and RESTful API skills.
• Hands-on experience with PyTorch/TensorFlow and Hugging Face tooling.
• Cloud + MLOps expertise (Docker, CI/CD, MLflow).
• Proven track record moving AI models to production.

Responsibilities

• Design, build, and deploy end-to-end ML/AI models.
• Develop GenAI apps using LLMs, RAG pipelines, and fine-tuning.
• Create scalable AI data pipelines and integrate with product APIs.
• Deploy models in production with Docker/Kubernetes and ensure monitoring.
• Benchmark latency, accuracy, and cost for enterprise-grade AI.
• Collaborate with data engineers, product managers, and backend teams.

Skills

Python

SQL

RESTful API development

Model deployment

Analytical thinking

Education

B.E./B.Tech./M.Tech./MS in CS/DS/AI

Tools

PyTorch

TensorFlow

Hugging Face

LangChain/LlamaIndex

Vector Databases

Docker

CI/CD

MLflow

AWS

Azure

GCP

Job description

Roles and Responsibilities

• Develop AI Solutions: Design, build, and deploy end-to-end Machine Learning, Deep Learning, and Generative AI models.
• Implement GenAI & LLMs: Develop advanced Generative AI applications using Large Language Models (LLMs), RAG pipelines, and fine-tuning techniques.
• Build AI Pipelines: Create scalable data pipelines, feature stores, and integrate AI models with core product APIs.
• Manage MLOps: Deploy models in production using Docker and Kubernetes, ensuring proper tracking, versioning, and monitoring.
• Optimize Performance: Evaluate and benchmark model latency, accuracy, and cost to ensure enterprise-grade efficiency.
• Collaborate Cross-Functionally: Work closely with Data Engineers, Product Managers, and Backend Teams to align AI capabilities with business goals.

Preferred Candidate Profile

• Education: B.E. / B.Tech / M.Tech / MS in Computer Science, Data Science, AI, or a related quantitative field.
• Experience: Minimum 3years of professional experience as an AI/ML Engineer, with at least 10 years focused on Generative AI and LLMs.
• Core Coding: Strong, production-grade programming skills in Python, SQL, and RESTful API development.
• Framework Mastery: Hands‑on experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex, and Vector Databases.
• Cloud & DevOps: Proven expertise in AWS, Azure, or GCP, alongside MLOps tools (Docker, CI/CD, MLflow).
• Problem Solving: Excellent analytical skills with a track record of moving AI models from research to production.