mParticle by Rokt is widely recognized as one of the leading customer data platforms, serving hundreds of global brands and helping them turn data to insights and insights to action. Built on top of end-to-end streaming architecture, we are committed to empowering businesses to deliver personalized and engaging experiences to their customers across all screens and devices. We believe that the opportunity to help teams activate insights from their customer data to deliver more relevant and adaptive experiences is more important than ever. In January 2025 mParticle merged with Rokt and became mParticle by Rokt. Together, our AI and ML-powered Rokt Brain and ecommerce Rokt Network will power more than 6.5 billion transactions, connecting 400 million customers across the world’s leading companies.
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 mParticle by 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.
At Rokt, we practice transparency in career paths and compensation. At Rokt, we believe in transparency, which is why we have a well-defined career ladder with transparent compensation and clear career paths based on competency and ability. Rokt’stars constantly strive to raise the bar, pushing the envelope of what is possible.
We are looking for a Senior Machine Learning Engineer
Total Compensation between: $325,000-435,000, which includes a fixed annual salary between $225,000 - $285,000, employee equity plan grant & world class benefits.
Equity grants are issued in good faith, subject to company policies, board approval, and individual eligibility.
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, lookalike modelling, forecasting, etc.
About the Role:
- Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions.
- 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.
- Keep track of emerging tech and trends, research the state-of-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments.
- 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
- Extensive 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.
- 3+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring.
- Experience with Kubeflow (or similar), Tensorflow and Feature Store in a production environment is a massive plus.
- 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, ESMM, xDeepFM, and GDCN.
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