5 days ago
Responsibilities
- Design and implement scalable batch and real-time machine learning pipelines for advertising delivery and optimization.
- Operationalize machine learning models and integrate them with ad delivery, bidding, ranking, and campaign management systems.
- Build and maintain data pipelines for large-scale advertising impressions, clicks, and conversion data.
- Enable low-latency inference and real-time decision-making across advertising systems and multiple brands.
- Develop reusable components, APIs, and orchestration workflows for experimentation, deployment, and iteration.
- Monitor, optimize, and improve the reliability, scalability, and performance of production ML-powered advertising systems.
- Collaborate with software engineering, data science, product, platform, analytics, and business teams.
- Set technical direction, raise engineering standards, and mentor other team members.
Requirements
- Bachelor’s or master’s degree in computer science, engineering, data science, or a related quantitative field.
- At least 4 years of industry experience working with machine learning or data-driven systems.
- Proficiency in Python and familiarity with machine learning frameworks such as PyTorch or TensorFlow.
- Understanding of supervised learning, feature engineering, model evaluation, and basic bias/variance tradeoffs.
- Experience with data pipelines and large datasets using tools such as Spark, SQL, or similar technologies.
- Familiarity with software engineering fundamentals, including version control, testing, and basic system design.
- Ability to collaborate effectively and communicate technical concepts clearly.
- Preferred: experience contributing to production ML systems, including training, evaluation, or inference pipelines.
- Preferred: familiarity with Spark, Databricks, AWS, MLOps, model monitoring or retraining workflows, and real-time ML systems.
- Preferred: experience with ranking, prediction, classification, recommendation, or NLP models and interest in advertising, marketplaces, e-commerce, or travel platforms.
Benefits
- Medical, dental, and vision coverage.
- Paid time off, an Employee Assistance Program, wellness reimbursement, and travel reimbursement.
- Travel discounts and International Airlines Travel Agent Network membership.
- Available only in San Jose, California or Seattle, Washington, with at least three days per week in the office.
- Relocation assistance is not available.
Tech Stack
Categories
Data EngineeringML Engineering
