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 .