Lead Machine Learning Engineer / Senior Staff Applied Scientist

Rokt, a rapidly growing ecommerce technology company valued at $3.5 billion USD, is seeking a Lead Machine Learning Engineer/Senior Staff Applied Scientist to join their engineering team. This role offers an exceptional opportunity to lead cutting-edge ML research and development, working with systems that handle millions of transactions daily and process billions of data points. The position combines technical leadership with hands-on development, requiring expertise in advanced ML concepts including reinforcement learning, multi-task learning, and deep learning architectures.

The role involves leading a high-caliber team of Applied Scientists while working on sophisticated ML-driven systems that power over 6.5 billion transactions annually. You'll be responsible for researching, designing, and deploying models that advance recommender systems, conversion optimization, and user experience enhancement. The position offers competitive compensation ranging from $375,000 to $515,000, including equity, and comes with comprehensive benefits.

Rokt's platform connects over 400 million customers to world-leading companies, helping businesses unlock real-time relevancy at crucial purchasing moments. The company's commitment to innovation and growth is evident in their 40%+ annual revenue growth over the past decade. This role offers the unique opportunity to work with best-in-class technology and market-leading innovation in AI and ML, while being part of a mission-driven, diverse team that values transparency and smart, humble people.

The ideal candidate will bring deep expertise in machine learning, a proven track record of driving impact, and the ability to lead and mentor other team members. You'll be working in a collaborative environment that encourages continuous learning, with access to a $5,000 annual training allowance and opportunities for career advancement. The role is based in Surry Hills, Australia, with a hybrid work arrangement requiring 4 days in the office, offering the perfect balance between collaborative work and flexibility.