RZR Global Inc.

RZR Global Inc.

Machine Learning Engineer

San Francisco · Senior

Sponsorship not specifiedDetected 92 days ago
PythonRustC++SQLRESTgRPCKafkaMachine LearningTensorFlowPyTorchscikit-learnSparkData AnalysisData EngineeringStatisticsForecastingSignal ProcessingCommunication

About the role

  • We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team.
  • As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP).

Responsibilities

  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Document experiments, assumptions, and outcomes
  • maintain reproducibility

Requirements

  • Required Skills / Experience

Nice to have

  • Familiarity with system programming languages including C++ and Rust is a plus.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.
  • Analyze the impact of integrating new data sources and features into our models.
  • Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.
  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.

Benefits

  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
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