Position Summary
At Liftoff, the Supply ARO team is crucial to the success of our Publisher side business. Our team is dedicated to designing and building advanced machine learning models that process over a billion events daily, driving significant impact and value. We are rapidly expanding and are a group of innovative engineers leveraging the latest technology to develop efficient and scalable systems.
If you're passionate about building and scaling low-latency, high-throughput systems and have a keen interest in machine learning, we would love to speak with you!
Location
This is a remote-first role, requiring:
- Ability to work Pacific time zone hours.
- Willingness to travel to Orange County for in-person meetings 1-2 weeks per quarter.
Liftoff is a remote-first company with US hubs in Redwood City, Los Angeles, San Francisco, Orange County, and NYC. Given that most of the team is based in Orange County, it would be beneficial for the individual to be located in the OC/Los Angeles area for regular in-person meetings at our OC office (Costa Mesa, CA 92626). Most of the local team meets in-office once per week. We are also open to candidates located on the West Coast who are willing to travel regularly (one week per quarter) to the OC office.
Key Responsibilities
- Develop and train machine learning algorithms to dynamically identify and prioritize high-value inventories for Real-Time Bidding (RTB) buyers.
- Continuously explore and reassess previously underperforming inventories to capture opportunities when buyer demand shifts positively.
- Utilize existing machine learning infrastructure and enhance it as needed to support optimization goals, ensuring scalability and efficiency for processing high-throughput, low-latency bid requests.
- Design, execute, and oversee experiments to test different optimization strategies, ensuring offline estimations closely mirror online revenue estimations using techniques such as counterfactual estimation and inverse propensity score methods.
- Perform statistical analysis on experiment results to fine-tune algorithms and improve performance.
- Collaborate with other engineering teams to ensure a robust data pipeline, logging, and aggregating data efficiently and effectively, allowing ML models to leverage this data in bidder technology.
- Participate in fostering an “engineering excellence” culture through the adoption of state-of-the-art tools, risk-driven testing, explainable systems, and rigorous code reviews.
Qualifications
- BS/MS degree in Computer Science, Data Science, Mathematics, or a related field.
- 12+ years of total professional technical experience.
- 5+ years of experience as a Software Engineer.
- 8+ years of experience leading and executing machine learning projects.
- Deep expertise in machine learning algorithms.
- Extensive practical experience with ML frameworks and libraries.
- Proficiency in at least one of the following programming languages: Python, Go, R, C++, or Java.
- In-depth knowledge of distributed systems and data processing frameworks.
- Strong problem-solving and analytical skills.
- Experience with data visualization tools such as Tableau or Looker.
- Ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
- Highly self-motivated and comfortable working in a dynamic, fast-paced environment.
- Strong passion for learning and contribution to team success.
Preferred Experience
- Experience in the Ad Tech industry.
- Strong mathematical background, particularly in statistics.
- Experience in Data Engineering and Feature Stores.
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