AI Engineer

Houghton Mifflin Harcourt; Maharashtra; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Houghton Mifflin Harcourt (HMH) is seeking a mid-level AI Engineer to build scalable, production-ready AI solutions that support analytics, automation, and intelligent decision-making. You will contribute to ML model development, GenAI systems, and AI-enabled data workflows across platforms.

You will design and deploy models with TensorFlow and PyTorch, implement LLMs using LangChain, and collaborate with data engineers to ensure robust data pipelines.

Qualifications

• 3–5 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.

Responsibilities

• Design, train, and deploy ML/DL models using TensorFlow, PyTorch, and Scikit-learn.
• Implement and fine-tune large language models (LLMs) using LangChain, RAG, and vector databases.
• Use MLflow and Docker to manage model lifecycle, reproducibility, and scalability for GenAI systems.
• Collaborate with data engineers to ensure robust data pipelines for model training and inference.
• Develop APIs and microservices to integrate AI models into enterprise applications and workflows.
• Continuously monitor model performance and retrain as needed to maintain accuracy.
• Ensure AI systems comply with enterprise security and data governance standards.

Skills

Python

AI/ML engineering

RESTful APIs

Microservices

NLP

Computer vision

Tools

TensorFlow

PyTorch

Scikit-learn

LangChain

Docker

MLflow

Job description

HMH is a learning technology company committed to delivering connected solutions that engage learners, empower educators and improve student outcomes. As a leading provider of K–12 core curriculum, supplemental and intervention solutions, and professional learning services, HMH partners with educators and school districts to uncover solutions that unlock students’ potential and extend teachers’ capabilities.

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

• 3–5 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.