Machine Learning Lead - Python

About the Role :

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

Were 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.
Youll 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 Youll 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 Were Looking For :

Core Skills & Experience :

- 8-10 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.