Moloco is looking to solve challenging problems in a complex multi-causal environment within their ML-powered performance ads business by determining bidding/pricing decisions, driving performance improvements and cost reductions, and stabilizing their core system.
Requirements
- Proven experience working in the adtech space—preferably with exposure to auction-based systems and real-time bidding environments.
- Strong mathematical or statistical background (e.g., optimization, probability, hypothesis testing).
- Strong system design skills, with experience in designing scalable, fault-tolerant distributed systems.
- Familiarity with cost-aware engineering practices—ability to optimize for compute, memory, and latency trade-offs.
- Hands-on coding ability in production-level codebases (e.g., C++, Java, Go, or Python).
- Working knowledge of machine learning principles, particularly in applied settings like ranking, predictions, or decision systems.
- Ph.D degree in Applied Mathematics, Operations Research, Management Science or related field a plus.
Responsibilities
- Design and implement real-time bidding and pricing algorithms for a high-scale advertising system (7M QPS), using optimization techniques, auction theory, and machine learning fundamentals.
- Leverage adtech experience to improve auction outcomes and bidding strategies, drawing from a strong understanding of advertising ecosystem dynamics (e.g., DSPs, SSPs, auctions).
- Develop scalable and cost-efficient ad serving systems, with strong system design principles to support performance advertising at scale.
- Conduct deep root-cause analyses of ad performance issues, using statistical reasoning and quantitative methods to drive unbiased insights and corrective actions.
- Identify opportunities to optimize the ad delivery pipeline, including reducing system or serving costs while maintaining performance, using efficient algorithms and data structures.
- Collaborate cross-functionally with product, infra, and account teams to anticipate the business impact of system changes and define future product roadmaps with a strong sense of product intuition and operational awareness.
- Stay informed on system-level and data-level changes, and work with collaborators to improve infrastructure and ML model performance in response.
Other
- 6+ years of overall work experience (industry or postgraduate) in research related fields focused on optimization of market prices or ML systems
- Solid understanding of business metrics, with an ability to translate technical changes into business outcomes.
- Lead research projects and may lead small teams of MLEs as part of a broader group of cross functional collaborators
- Bachelor's Degree in Computer Science with mathematical (ex, stats) coursework
- Creating a diverse workforce and a culture of inclusion and belonging is core to our existence.
