AI Engineer

HMH Technology Private Limited; Pune District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

HMH Technology Private Limited seeks a mid-level AI Engineer to build scalable, production-ready AI solutions supporting analytics, automation, and decision-making. You will contribute to ML model development, generative AI systems, and AI-enhanced data workflows across platforms.

The role involves deploying models with TensorFlow/PyTorch, fine-tuning LLMs, and managing end-to-end pipelines using MLOps tools, LangChain, and vector databases.

Qualifications

• 35 years of experience in AI/ML engineering or related roles.
• Proficiency in Python and experience with AI frameworks (TensorFlow, PyTorch).
• Familiarity with cloud platforms (AWS, Azure, GCP) for model deployment.
• Experience with MLOps tools (MLflow, Docker) and GenAI deployment.
• Strong understanding of LLMs, NLP, and computer vision techniques.
• Ability to write clean, efficient, and reusable code.
• Experience with RESTful APIs and microservices architecture.

Responsibilities

• Model Development Deployment: Design, train, and deploy ML/DL models.
• Generative AI LLMs: Implement and fine-tune LLMs using LangChain and related tools.
• MLOps GenAIOps: Use MLflow and Docker to manage model lifecycle and scalability.
• Data Engineering Collaboration: Work with data engineers to ensure robust pipelines.
• Integration APIs: Develop APIs and microservices to integrate models into AB workflows.
• Monitoring Optimization: Continuously monitor model performance and retrain as needed.
• Security Governance: Ensure AI systems comply with security and governance standards.

Skills

Python

AI frameworks

Cloud platforms

MLOps

LLMs/NLP/Computer Vision

RESTful APIs

Tools

MLflow

Docker

LangChain

Vector databases

Job description

Position Summary

We are seeking a mid-level AI Engineer to join our team focused on building scalable, production-ready AI solutions that support analytics, automation, and intelligent decision-making. This role will contribute to the development and deployment of machine learning models, generative AI systems, and AI-enhanced data workflows across platforms.

Key Responsibilities

• Model Development Deployment: Design, train, and deploy machine learning and deep learning models using frameworks like TensorFlow, PyTorch, and Scikit-learn.


• Generative AI LLMs: Implement and fine-tune large language models (LLMs) using tools such as LangChain, RAG, and vector databases. Experience with GPTs, LLaMA, or similar models is preferred


• MLOps GenAIOps: Use tools like MLflow and Docker to manage model lifecycle, reproducibility, and scalability. Support production-grade GenAI systems


• Data Engineering Collaboration: Work closely with data engineers to ensure robust data pipelines and infrastructure for model training and inference.


• Integration APIs: Develop APIs and microservices to integrate AI models into enterprise applications and workflows.


• Monitoring Optimization: Continuously monitor model performance and retrain as needed to maintain accuracy and relevance.


• Security Governance: Ensure AI systems comply with enterprise security and data governance standards.

Skills Qualifications

• 35 years of experience in AI/ML engineering or related roles.


• Proficiency in Python and experience with AI frameworks (TensorFlow, PyTorch).


• Familiarity with cloud platforms (AWS, Azure, GCP) for model deployment.


• Experience with MLOps tools (MLflow, Docker) and GenAI deployment.


• Strong understanding of LLMs, NLP, and computer vision techniques.


• Ability to write clean, efficient, and reusable code.


• Experience with RESTful APIs and microservices architecture.

Preferred Experience

• Exposure to educational technology or enterprise data environments.


• Experience integrating AI into transactional systems.


• Familiarity with data warehouses and data governance frameworks.