Lead AI Feature Engineer

Accountabilities:

• • Discover, develop, and maintain high-quality features from enterprise, scientific, laboratory, and instrument data to improve the performance, reliability, and explainability of ML and AI solutions.
  • Design and execute data exploration, feature engineering, and feature-selection experiments to identify meaningful signals, validate assumptions, and optimize model performance.
  • Build reusable feature data products, feature stores, and feature-generation pipelines that can support multiple models, solutions, and business environments.
  • Establish and promote best practices for feature quality, lineage, monitoring, documentation, and lifecycle management.
  • Ensure feature assets remain reliable, traceable, scalable, and production-ready throughout their lifecycle.
  • Partner with Data Scientists, AI Scientists, AI Engineers, Product Owners, and Architects to translate complex business and scientific challenges into reusable feature assets and predictive capabilities.
  • Apply statistical and machine learning techniques to identify valuable patterns and signals within complex datasets.
  • Contribute to scalable data-processing and feature-engineering practices that enable high-performing analytics, machine learning, and AI solutions.

  Requirements:

  • Strong hands-on experience in Data Science, Machine Learning, feature engineering, and predictive modeling, including developing production-quality features for machine learning solutions.
  • Deep understanding of data preparation, feature extraction, dimensionality reduction, feature selection, statistical analysis, and model performance optimization.
  • Strong proficiency in Python and SQL, along with experience using notebooks, machine learning libraries, and modern data-processing frameworks.
  • Experience building scalable data pipelines, feature-generation workflows, and reusable feature assets in cloud-based environments.
  • Strong analytical and problem-solving abilities, with the ability to identify valuable signals within complex data and translate them into measurable outcomes.
  • Ability to collaborate effectively with multidisciplinary teams and communicate technical concepts clearly to technical and business stakeholders.
  • Experience building feature stores, reusable feature repositories, or feature-engineering frameworks is a plus.
  • Experience with predictive modeling approaches such as gradient boosting, ensemble methods, Bayesian modeling, optimization algorithms, forecasting, or advanced statistical techniques is desirable.
  • Experience working with life sciences, diagnostics, healthcare, laboratory environments, advanced manufacturing, or other data-rich scientific industries is advantageous.

  Benefits:

  • Full-time position based in India.
  • Remote work arrangement, allowing eligible employees to work from home.
  • Comprehensive and competitive employee benefits programs.
  • Healthcare benefits designed to support employee well-being.
  • Paid time off.
  • Flexible working arrangements for eligible roles.
  • Opportunity to work on production-grade AI, machine learning, and data products with enterprise-scale impact.
  • Exposure to multidisciplinary teams across Data Science, AI Engineering, Product, Architecture, and Data Engineering.
  • Opportunity to work with complex scientific, laboratory, enterprise, and instrument data.
  • Professional growth opportunities within a global technology and science-focused environment.