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Machine Learning Engineer role to design, build, and deploy ML models for personalization, predictive analytics, and automated decision-making. Requires Python, TensorFlow or PyTorch, vector databases, LLM deployment in production, and AWS, Postgres, Redis, and Snowflake experience. Ruby experience is a plus; 5+ years in ML or data roles required.
Hang is building the future of loyalty for brands.
Hang is the next generation brand loyalty & membership platform. By harnessing the power of personalization, gamification, and its integrations ecosystem, Hang provides brands with a radically new type of loyalty experience for their customers.
Today, they work with a variety of major brands (such as Ulta Beauty, Budweiser, Flipkart, and more), as well as multiple well-known, up-and-coming restaurant chains (Boba Guys, Roam Artisan Burger, and Williamsburg Pizza, among several others).
Hang draws from years of deep expertise in loyalty, game design, and finance with employees from leading companies like Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs.
Hang raised a $16 million Series A led by Paradigm last summer, with participation from Tiger Global, Howard Schultz, Kevin Durant, Mr. Beast, and the founders of Warby Parker, Allbirds, and Bombas, among others.
About the Role
We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform's capabilities, making key contributions to our product development, and driving data-driven decision-making.
What You’ll Do
Who You Are
What Would Set You Apart
Benefits
