About Us

Aarki is an AI company that builds advertising solutions to drive mobile revenue growth. We use AI to find audiences in a privacy-first world by using trillions of contextual bidding signals coupled with proprietary neural net based models. Our platform includes a full-service team and Unified Creative Strategy that delivers ad creative ideation and execution. We have worked with hundreds of advertisers over 14 years and see 5M mobile ad requests per second from over 10B devices driving performance for publishers and brands. It is independently operated and headquartered in San Francisco, CA with offices 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 data scientists and other team members to drive impactful machine learning projects and contribute to innovative solutions.

This is an on-site role, based in our San Francisco office.

Join us in pushing the boundaries of AI and mobile advertising in a collaborative environment that fosters creativity and growth. We offer a competitive salary, comprehensive benefits, and significant opportunities for career advancement.

Role & 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 business) 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. Learn and stay informed about emerging techniques in machine learning and data science, applying them as appropriate to enhance our products. Skills & Experience Bachelor's degree in Mathematics, Physics, Computer Science, or a related technical field. At least 1 year of professional experience in machine learning, statistical analysis, and data analysis. Proficiency in Python and SQL. Experience with machine learning techniques such as regression, classification, and clustering. 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. Familiarity with AdTech, personalization and pricing algorithms, or system programming languages including C++ and Rust is a plus.