Software Engineer, Machine Learning (Ads)

Location: Hybrid role with in-office time expected in Sunnyvale, CA; San Francisco, CA; Seattle, WA; or New York, NY.

Salary: $137,100–$201,600 USD, $167,800–$246,800 USD, or $203,500–$299,300 USD annually, depending on level and work location. Equity grants may also be available.

Company

hirify.global operates an on-demand logistics and delivery platform connecting Consumers, Merchants, and Dashers.

What you will do

• Develop machine learning models to improve advertising efficiency and quality.
• Design optimization algorithms for budget pacing and automated bidding.
• Analyze bid density, market competitiveness, advertising value, and platform revenue.
• Develop data solutions such as embeddings and consumer profiles for audience targeting.
• Own the end-to-end ML lifecycle, including ideation, offline training, online shadowing, deployment, experimentation, and monitoring.
• Extend data and ML infrastructure and scale systems supporting advertising applications.

Requirements

• Master’s degree or PhD in computer science, mathematics, statistics, physics, or a related technical field, or equivalent experience.
• 3+ years of industry machine learning experience and strong knowledge of ML algorithms and fundamentals.
• Experience building large-scale data and feature engineering pipelines with PySpark and Snowflake SQL.
• Experience building production ML systems with PyTorch, Keras, LightGBM, scikit-learn, Spark ML, or related frameworks.
• Ability to work in a hybrid arrangement with regular in-office time in one of the listed US locations.

Nice to have

• Experience in online advertising.
• Experience with search relevance and ranking.
• Experience with recommendation systems.

Culture & Benefits

• 401(k) plan with employer matching.
• Medical, dental, vision, disability, and basic life insurance.
• Paid parental leave, paid time off, paid sick leave, and 11 paid holidays.
• Wellness, commuter, family-forming, and mental health benefits.
• Flexible paid time off for salaried roles.