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 .