Principal Applied Scientist/Machine Learning Engineer

About Rokt

Rokt is the global leader in eCommerce technology, helping companies seize the full potential of every transaction moment to grow revenue and acquire new customers at scale. Live Nation, AMC Theatres, PayPal, Uber, Hulu, Staples, Lands’ End, and HelloFresh are among the more than 2,500 leading global businesses and advertisers that use Rokt's solutions to drive more value through every transaction by offering highly relevant messages to their customers at the moment they are most likely to convert.

With our December 2022 secondary transaction, Rokt’s valuation increased to $2.4 Billion. We are expanding rapidly and globally – operating in 14 countries across North America, Europe and the Asia-Pacific region with the largest office in Sydney and a major R&D hub in NYC. With 50% annual growth and vibrant company culture, Rokt has been listed in ‘Great Places to Work’ in the US and Australia. Our award-winning culture is guided by our eight core values: smart with humility, own the outcomes, force for good, conquer new frontiers, enjoy the ride, raise the bar, communicate with impact, and disagree then commit. These values help us attract, engage, and develop the right talent around the globe and ensure we foster an environment that helps us all do our best work. Keen to join a fast-growing company and a vibrant culture? Learn more at rokt.com.

The Rokt engineering team builds best-in-class eCommerce technology that provides personalised and relevant experiences for customers globally and empowers marketers with sophisticated, AI-driven tooling to better understand consumers. Our bespoke platform handles millions of transactions per day and considers billions of data points which gives engineers the opportunity to build technology at scale, collaborate across teams and gain exposure to a wide range of technology. We are expanding rapidly in our major R&D centres in NYC and Sydney. We are passionate about using intelligent systems to improve the transaction moment for retailers everywhere. Come join us and build the future!

About the role

As a Principal Scientist/Machine Learning Engineer you will be able to drive the future direction of new initiatives and push the boundaries on what the world thinks is possible by leveraging the latest advancements in ML. You will join a team of top-tier Machine Learning Engineers and be an inherent part of the Relevancy org and will be responsible for driving machine learning solutions from research to production.

Your expertise will be critical in designing, implementing and scaling innovative machine learning solutions that drive impact across the business. Reporting to the VP of Engineering (AI/Data) you will work closely with product managers, machine learning engineers and software engineers to understand business priorities, frame ML problems and architect solutions that deliver real-world value specifically in CTR modelling, Conversion modelling, UX optimisation, price optimisation and NLP.

In this role you will be encouraged to keep up with emerging trends in machine learning, research state of the art deep learning architectures, prototype new modelling ideas and conduct offline and online experiments and deploy your solutions to production.

Responsibilities

• Develop and implement machine learning algorithms to solve business problems
• Design and implement scalable data processing and machine learning pipelines
• Collaborate with product, engineering, and data teams to identify machine learning opportunities
• Evaluate and improve the performance of machine learning models
• Stay up-to-date with the latest developments in machine learning research and apply them to real-world problems
• Write clean, scalable, and maintainable code
• Communicate technical concepts and ideas to both technical and non-technical stakeholders
• Sharing your knowledge by giving brown bag sessions, tech talks, and evangelising appropriate tech and engineering best practices.
• Mentoring other team members, facilitating within/across team workshops, and leading agile development.

Requirements

• PhD or Masters's Degree in Computer Science, Mathematics, or Statistics a similar technical field of study with a specialisation in Machine Learning, Data mining, Information Retrieval or Data science.
• 10+ years of industry experience in building production-grade machine learning systems with all aspects of research, model training, tuning, deploying, serving and monitoring. Industry experience in ecommerce, recommender systems, digital marketing or two-sided marketplaces is a plus.
• Experience in the following areas - Bayesian methods, Reinforcement learning, Deep learning Architectures and Recommendation systems and if you have experience in ML for Ads or ecommerce it is a