Machine Learning Lead
2 days ago
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.
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