ML Engineer Lead (full time)

Machine Learning Engineer Lead

Hiring Machine Learning Engineer Lead for our client, which is a global digital engineering company specializing in data engineering, cloud solutions, and enterprise AI services.

Python | PySpark | AWS | MLOps

Location : Noida / Gurgaon / Indore / Bangalore / Pune

Experience : 8-10 years | Full-time

About the Role

Are you passionate about building scalable AI / ML systems that make real-world impact?

We’re looking for a Senior Machine Learning Engineer with strong expertise in Python , PySpark , and AWS to design and deploy data-driven solutions that power intelligent decision-making across our organization.

You’ll work at the intersection of data engineering, data science, and MLOps — collaborating with cross-functional teams to build, deploy, and optimize production-grade machine learning systems at scale.

What You’ll Do

Design, develop, and maintain feature and data pipelines using PySpark and AWS tools.

Collaborate with data scientists, engineers, and product teams to build scalable ML solutions from concept to deployment.

Leverage AWS services such as SageMaker, Bedrock, and Kendra for advanced AI model development and deployment.

Apply expertise in data science , statistics , and machine learning to create predictive and analytical models.

Implement MLOps practices — including model management, deployment, monitoring, and continuous improvement.

Conduct exploratory data analysis (EDA) and derive actionable insights for business outcomes.

Work on diverse ML domains including Time Series Forecasting, NLP, Image / Video Analytics , and Generative AI .

Drive innovation and knowledge sharing within the team, fostering a culture of continuous learning and experimentation.

What We’re Looking For

✅ Core Skills & Experience

5+ years of experience in Python and PySpark development for feature / data pipelines.

Proven track record in AI / ML system development and MLOps implementation at scale.

Strong understanding of statistical modeling (e.g., multinomial logistic regression) and data science methodologies .

Hands-on experience with AWS cloud services (SageMaker, Bedrock, Kendra, etc.).

Deep knowledge of ML lifecycle : data collection, preparation, feature engineering, model management, deployment, and monitoring.

Proficiency in statistics (probability distributions, hypothesis testing) and model evaluation metrics .

Exposure to time series modeling , forecasting , NLP , and image / video analytics .

✅ Bonus / Good to Have

Experience with Large Language Models (LLMs) and Generative AI .

Familiarity with LangChain, LLAMAIndex , and foundation model tuning .

Knowledge of Docker and Kubernetes for scalable ML deployments.

Experience with data augmentation , performance evaluation frameworks , and AI pipeline optimization .

Why Join Us?

Work on cutting-edge AI and Generative AI projects impacting real business outcomes.

Collaborate with top-tier engineers, data scientists, and innovators.

Grow your technical and leadership skills in a fast-paced, data-driven environment.

Be part of a culture that values curiosity, creativity, and continuous learning .