Senior Machine Learning Engineer

We are Rokt, a hyper-growth ecommerce leader. 

Rokt is the global leader in ecommerce, unlocking real-time relevance in the moment that matters most. Rokt’s AI Brain and ecommerce Network powers billions of transactions connecting hundreds of millions of customers and is trusted to do this by the world’s leading companies.

We are a team of builders helping smart businesses find innovative ways to meet customer needs and generate incremental revenue. Leading companies drive 10-50% of additional revenue—and often all their profits—from the extra products or services they sell. This economic edge unleashes a world of possibilities for growth and innovation.

The Rokt engineering team builds best-in-class ecommerce technology that provides personalized and relevant experiences for customers globally and empowers marketers with sophisticated, AI-driven tooling to understand consumers better. Our bespoke platform handles millions of transactions per day. It considers billions of data points which give engineers the opportunity to build technology at scale, collaborate across teams and gain exposure to a wide range of technology.

We are looking for a Senior Machine Learning Engineer

Target Total Compensation: $300,000 - $435,000, including a fixed annual salary of $200,000 - $285,000, employee equity grant, and world-class benefits.

As a Senior Machine Learning Engineer, you are someone who has significant expertise in both machine learning and software engineering. You will be working with our engineering and product teams to design, build and productionise proprietary machine learning models to solve different business challenges including smart bidding, budget pacing, lookalike modelling, and more.

What You’ll Do

• Build and productionise machine learning models including data preparation/processing pipelines, machine learning orchestrations, improvements of services performance and reliability and etc.
• Contribute and maintain the high quality of the code base with tests that provide a high level of functional coverage as well as non-functional aspects with load testing, unit testing, integration testing, etc.
• Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions.
• Share your knowledge by giving brown bags, tech talks, and evangelising appropriate tech and engineering best practices.

About You:

• Masters or PhD in Machine Learning
• 3+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring
• Good Knowledge in AWS, Kubeflow (or similar), Tensorflow and Feature Store in a production environment.
• Good knowledge in and experience with some of the following areas - Bayesian methods, Recommender systems, multi-task modelling, meta-learning, click through rate modelling or conversion rate modelling
• Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned in this benchmark: DCNV2, MMOE, Deep & Wide and ESMM