Machine Learning Engineer - L3

Posted 4 Days Ago
Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Junior
AdTech • Artificial Intelligence • Machine Learning • Marketing Tech • Software
The Role
Develop and support machine learning models and data pipelines for a programmatic DSP, collaborate with cross-functional teams to integrate models into production, analyze new data sources, maintain reproducible experiments, and help evaluate tools and methodologies.
Summary Generated by Built In

Who are we?

RZR  is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.

Role Overview

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). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.

Key Responsibilities
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Analyze the impact of integrating new data sources and features into our models.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • Document experiments, assumptions, and outcomes; maintain reproducibility
Required Skills / Experience
  • Bachelor’s degree in Mathematics, Physics, Computer Science, or a related technical field.
  • 1-3 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • 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.
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.

 

Skills Required

  • Bachelor's degree in Mathematics, Physics, Computer Science, or related technical field.
  • 1-3 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • Proficiency in Python and SQL.
  • Familiarity with big data tools (e.g., Spark).
  • Familiarity with ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team and communicate complex concepts to diverse stakeholders.
  • Familiarity with system programming languages including C++ and Rust.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink).
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.
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The Company
HQ: San Francisco, California
65 Employees

What We Do

RZR powers performance for the world's most ambitious brands through proprietary neural architecture that optimizes across user acquisition, retargeting, CTV, and influencer campaigns as one connected performance system. With four owned-and-operated data centers that process 6M+ queries per second, RZR turns signals into strategy and impressions into impact. Trusted by brands across gaming, consumer, food and beverage, retail, and entertainment. Built on over a decade of performance data and backed by AI and ML experts and industry veterans across offices in San Francisco, New York, London, Bangalore, Beijing, Manila, and Seoul. RZR delivers retention-led growth intelligence: faster, sharper, and built for performance at scale.

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