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RoktRoktAustin, TX

Senior Machine Learning Engineer

Senior Machine Learning Engineer building and productionizing proprietary ML models for smart bidding, lookalikes, forecasting, ranking and prediction at Rokt's ecommerce recommendation platform. Requires advanced degree, production ML systems experience, and expertise in areas like recommender systems or CTR modelling.

335k – 400k/yr
Hybrid7+ YOEML Engineering

About the role

Responsibilities

  • 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.

Requirements

  • 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.
  • Willingness to work 4 day in-office, 1 day remote weekly schedule.

Compensation

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.

Skills

Machine LearningTensorFlowkubeflowbayesian methodsrecommender systemsmulti-task modellingmeta-learningclick-through rate modellingconversion rate modellingfeature engineeringmodel deploymentmodel monitoring

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