Home
Communities
Companies
- Companies
  
  Discover best places to work
- Compare Companies
  
  Compare & find best workplace
- Add Office Photos
  
  Bring your workplace to life
- Add Company Benefits
  
  Highlight your company's perks
Reviews
- Company reviews
  
  Read reviews for 6L+ companies
- Write a review
  
  Rate your former or current company
Salaries
- Browse salaries
  
  Discover salaries for 6L+ companies
- Salary calculator
  
  Calculate your take home salary
- Are you paid fairly?
  
  Check your market value
- Share your salary
  
  Help other jobseekers
- Gratuity calculator
  
  Check your gratuity amount
- HRA calculator
  
  Check how much of your HRA is tax-free
- Salary hike calculator
  
  Check your salary hike
Interviews
- Company interviews
  
  Read interviews for 40K+ companies
- Campus placements
  
  Interviews questions for 2K+ colleges
- Share interview questions
  
  Contribute your interview questions
Jobs
Awards

WINNERS AWAITED!
- ABECA 2025
  
  WINNERS AWAITED!
  
  AmbitionBox Employee Choice Awards - 4th Edition
- ABECA 2024
  
  AmbitionBox Employee Choice Awards - 3rd Edition
- AmbitionBox Best Places to Work 2022
  
  2nd Edition
- AmbitionBox Best Places to Work 2021
  
  1st Edition

Add office photos

Employer? Claim Account for FREE

Security and Intelligence Services (India)

Compare

4.2

based on 1.3k Reviews

Video summary

299 Security and Intelligence Services (India) Jobs

Lead - ML Engineering

S&P Global Inc.

4.2

based on 1.3k Reviews

9-13 years

Hyderabad / Secunderabad, Gurgaon / Gurugram, Bangalore / Bengaluru

1 vacancy

Lead - ML Engineering

Security and Intelligence Services (India)

posted 9d ago

Job Role Insights

Flexible timing

Key skills for the job

Python Supply Chain Management SQL Machine Learning Linux Administration GCP

+ 4 more

Job Description

As a Lead Machine Learning Engineer in the Document Platforms and AI Team, you will play a key role in building next-generation data extraction tools working on cutting-edge ML-powered products and capabilities that power natural language understanding, information retrieval, and data sourcing solutions for the Enterprise Data Organization and our clients.

This role offers an exciting opportunity to design, develop, and deploy production-ready machine learning models and data transformation pipelines, collaborating with engineers, data scientists, and product teams. You will lead by example, providing technical mentorship while remaining deeply hands-on in model development, deployment, and optimization. If you are passionate about AI, thrive in an innovative environment, and enjoy solving high-impact problems, we encourage you to apply!

The Impact:

The Document Platforms and AI Team has delivered breakthrough AI-powered solutions that have significantly influenced business outcomes over the past three years.
In this role, you will contribute to the next generation of AI-driven products, enhancing and optimizing existing solutions while developing new capabilities.

What s in it for you:

Be part of a global enterprise and build AI solutions at scale.
Work alongside a highly skilled and technically strong team.
Contribute to solving high-complexity, high-impact challenges in data transformation and machine learning.

Responsibilities:

Build production ready data acquisition and transformation pipelines from ideation to deployment.
Being a hands-on problem solver and developer helping to extend and manage the data platforms.
Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions
Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains.
Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training.
Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability.
Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability.
Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process.
Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions.
Code quality and best practices: Ensure high code quality and adherence to best practices for software development.
Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences.

What We re Looking For:

4+ years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps
Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face)
Experience with Apache Spark or other distributed computing frameworks for large-scale data processing.
AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks.
Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models .
Experience with CI/CD pipelines for ML models, including automated testing and deployment.
Docker Kubernetes experience for containerization and orchestration.
OOP Design patterns, Test-Driven Development and Enterprise System design
SQL (any variant, bonus if this is a big data variant)
Linux OS (e.g. bash toolset and other utilities)
Version control system experience with Git, GitHub, or Azure DevOps.
Excellent Problem-solving, Code Review and Debugging skills
Software craftsmanship, adherence to Agile principles and taking pride in writing good code
Techniques to communicate change to non-technical people