Feature AI/ML Engineer

Required Technical Skills

< class="" data-start="1091" data-end="1130">Programming & Data Engineering

• Advanced proficiency in Python and SQL.
• Strong expertise in distributed data processing frameworks such as Apache Spark and/or Apache Flink.
• Experience designing and implementing large-scale, production-grade data and feature engineering pipelines.

< data-start="1403" data-end="1450">Feature Engineering & Machine Learning

• Expertise in feature engineering techniques, advanced transformations, feature design patterns, and aggregation strategies.
• Strong understanding of data modeling for machine learning applications.
• Hands-on experience with enterprise feature store platforms such as Feast, Hopsworks, or Amazon SageMaker Feature Store.
• Good understanding of the ML lifecycle, including feature importance, feature selection, and model input optimization.
• Experience implementing data quality frameworks, validation pipelines, and drift detection mechanisms.

< data-start="2014" data-end="2051">Cloud & Platform Engineering

• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
• Knowledge of CI/CD pipelines, automated testing, and DevOps practices.
• Experience with monitoring, observability, production debugging, and performance tuning.
• Strong understanding of scalability, reliability, and production support for enterprise data platforms.

Professional Experience

• 6 10+ years of experience in Data Engineering, Feature Engineering, Machine Learning Engineering, or related disciplines.
• Proven experience designing, building, and supporting production-grade feature engineering and data pipelines.
• Demonstrated expertise in scalable distributed data systems.
• Experience working with enterprise AI/ML platforms, feature stores, and production ML ecosystems.
• Prior experience providing technical leadership, mentoring engineers, or leading engineering initiatives.

Leadership & Soft Skills

• Strong technical leadership and mentoring capabilities.
• Excellent collaboration skills across Data Science, ML Engineering, MLOps, Platform Engineering, and business stakeholders.
• Strong analytical, problem-solving, and optimization mindset.
• Ability to translate business requirements into scalable, production-ready feature engineering solutions.
• Excellent communication skills with the ability to influence technical decisions and drive engineering best practices.