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Antino Labs - AI / ML Engineer - Data Modeling

Antino Labs - AI / ML Engineer - Data Modeling

Antino Labs Private LimitedGurugram
30+ days ago
Job description

Job Description : About the Role :

We are seeking a talented AI / ML Engineer to join our innovative team. The ideal candidate will have a strong foundation in artificial intelligence and machine learning concepts, practical experience with model development, and the ability to implement end-to-end AI solutions. This role requires both theoretical knowledge and hands-on expertise to solve complex problems using data-driven approaches.

Key Responsibilities :

  • Design, develop, and deploy machine learning models to address business problems
  • Select appropriate algorithms based on specific use cases and requirements
  • Implement data preprocessing pipelines and feature engineering techniques
  • Train, evaluate, and fine-tune models using appropriate metrics and validation methods
  • Optimize model performance through hyperparameter tuning and architecture adjustments
  • Collaborate with data scientists, engineers, and product teams to integrate AI solutions
  • Monitor model performance and implement improvements as needed
  • Stay current with the latest advancements in AI / ML research and technologies

Required Skills & Qualifications :

  • Bachelor's degree in Computer Science, Data Science, Statistics, or related field (Master's preferred)
  • 2+ years of professional experience in AI / ML or related field
  • Strong understanding of core ML concepts including :

  • Various learning paradigms and their applications
  • Different types of ML problems (classification, regression, clustering)
  • Neural network architectures and their applications
  • Model evaluation metrics and performance assessment
  • Hyperparameter optimization methodologies
  • Proficiency in programming languages and ML frameworks
  • Experience with data preprocessing, normalization, and feature engineering
  • Knowledge of similarity search systems for efficient data retrieval
  • Understanding of activation functions and their impact on model performance
  • Ability to determine appropriate model architecture and complexity
  • Preferred Qualifications :

  • Experience implementing ensemble learning methods
  • Proficiency with various neural network architectures
  • Understanding of advanced vector search techniques
  • Experience with ML model deployment in production environments
  • Knowledge of different learning approaches for various use cases
  • Background in deep learning architecture design and optimization
  • Experience with large-scale data processing
  • ref : hirist.tech)

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