Senior Machine Learning Engineer

Posted 5 Hours Ago
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Austin, TX, USA
In-Office
210K-400K Annually
Senior level
Artificial Intelligence • Digital Media • eCommerce • Marketing Tech • Software • Automation
To unleash a world of possibilities by unlocking the moment that matters most
The Role
Design, build, and productionize machine learning models and data pipelines for recommendation, bidding, and forecasting. Collaborate with product and engineering teams, evaluate and monitor model performance, maintain high-quality tested code, prototype research ideas, and run experiments. Hybrid schedule: four days in-office, one remote.
Summary Generated by Built In

Rokt is an ecommerce technology company with the mission of making every transaction more relevant. The Rokt Ecommerce Network leverages proprietary machine learning recommendation systems, powering billions of transactions for hundreds of millions of customers, and is trusted to do this by companies like Live Nation, Fanatics, Macy's, AMC Theatres, PayPal, Uber, Hulu, Staples, Albertsons and HelloFresh.

We are hiring Senior Machine Learning Engineers

We are hiring engineers with 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.

Target total compensation ranges from $335k - $400k, comprised of a fixed annual salary of $210k - $260k, plus employee equity plan grant. In addition, you will receive world-class employee benefits.

Requirements

  • Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions for smart bidding, lookalike modelling, forecasting, and related ranking and prediction tasks.
  • Build and productionise machine learning models, including model-specific data pipelines, feature engineering within the team's feature store, and integration with the team's orchestration and serving infrastructure.
  • Evaluate model performance through offline metrics, and monitor deployed models for drift, leading retraining or rollback decisions as needed.
  • Contribute to 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 such as load testing, unit testing, and integration testing.
  • Keep track of emerging tech and trends, research the state-of-the-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments
  • Willingness to work 4 day in-office, 1 day remote weekly schedule.

Benefits

  • PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval (or equivalent experience)
  • 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 building production-grade machine learning systems, spanning model training, tuning, deployment, serving, and monitoring
  • Experience with Kubeflow (or similar), TensorFlow, and a 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: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN

Skills Required

  • Significant expertise in both machine learning and software engineering
  • PhD or Master's in Computer Science, Statistics, Mathematics, or related field or equivalent experience
  • Extensive knowledge and experience with Bayesian methods, recommender systems, multi-task modelling, meta-learning, CTR or conversion rate modelling
  • 3+ years industry experience building production-grade machine learning systems (training, deployment, serving, monitoring)
  • Experience with Kubeflow (or similar), TensorFlow, and a feature store in production
  • Familiarity with architectures/models such as DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, GDCN
  • Willingness to work four days in-office and one day remote each week

What the Team is Saying

Jon Humphrey
Julie Kremer
Shenika Louis
Nao Kobayashi
Dan

Rokt Compensation & Benefits Highlights

  • Healthcare Strength Health coverage includes multiple medical options with a zero‑cost monthly premium choice in the U.S., plus dental, vision, and mental‑health support through programs like Modern Health and a global EAP. Wellness resources and allowances, plus access to One Medical and family‑building partners in the U.S., reinforce breadth beyond core insurance.
  • Retirement Support U.S. employees are eligible for a dollar‑for‑dollar 401(k) match up to 4%, and all employees receive equity ownership. Financial planning tools and access to advisors are also described as part of the package.
  • Leave & Time Off Breadth The handbook outlines 20 paid days off with up to five bonus “High Five” days, a company holiday shutdown in late December/early January, and paid community service days. Paid parental leave of 16 weeks and references to sabbatical and other leaves extend the time‑off offering.

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The Company
HQ: New York, NY
800 Employees
Year Founded: 2012

What We Do

Rokt is the global leader in ecommerce, unlocking real-time relevance in the moment that matters most - The Transaction Moment. 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 including Live Nation, Macy’s, Fanatics, AMC Theatres, PayPal, Uber, Hulu, Staples, Albertsons and HelloFresh. Headquartered in New York City, Rokt has offices across North America, Europe, and the Asia-Pacific region. To learn more, visit Rokt.com.

Why Work With Us

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.

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We believe we are better together. We spend most of our time in the office (most teams are 4 days a week). One week per quarter, you also have the flexibility to work from anywhere.

Typical time on-site: None
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