Principal Data Scientist

2 days ago


Tirupati, Andhra Pradesh, India beBeeDataScience Full time ₹ 12,90,000 - ₹ 20,25,000
AI/ML Engineer – Bangalore

Job Overview:

  • Our organization seeks a skilled AI/ML Engineer with 2-5 years of experience to join our team in Bangalore.

Key Qualifications and Skills:

  • Expertise in time series analysis, including forecasting techniques and handling complex temporal datasets is mandatory.
  • A strong background in predictive modeling to analyze trends and enable data-driven decisions is also essential.
  • Hands-on experience in deploying and managing ML models on AWS infrastructure and tools is required.
  • Practical knowledge of Apache Kafka for real-time data streaming and scalable data pipelines is beneficial.
  • Strong programming skills in Python for model development, testing, and deployment are necessary.
  • Experience with Flask API for building and deploying ML model endpoints and RESTful services is advantageous.
  • Knowledge of model optimization techniques to improve predictive performance and efficiency is desirable.
  • Excellent debugging, troubleshooting, and production maintenance capabilities for AI/ML systems are required.

Responsibilities:

  • Develop, implement, and maintain machine learning models with an emphasis on time series forecasting and predictive analytics.
  • Build and optimize scalable data pipelines using Apache Kafka and AWS services.
  • Design, develop, and integrate Flask APIs to serve ML models into production-ready applications.
  • Collaborate with cross-functional teams and stakeholders to translate business requirements into AI-powered solutions.
  • Evaluate models, perform hyperparameter tuning, and apply optimization strategies for maximum efficiency.
  • Deploy, monitor, and maintain ML models in production, addressing data and performance issues proactively.
  • Document methodologies, experiments, and development processes for consistency and knowledge sharing.
  • Stay updated with advancements in AI, ML, and cloud technologies, recommending and implementing new approaches where relevant.


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