Software Engineer II, Advertiser OptimizationNew

The opportunity

The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, Targeting and advertiser-facing recommendations - converting stated advertiser goals into real-time auction actions.

What you'll do

  • Develop and evaluate models and algorithms for ads bidding, pacing, and: budgeting, applying your training in mathematics, statistics, economics, or a related quantitative discipline to solve complex marketplace problems at scale.

  • Collaborate closely with senior scientists, engineers and product managers to: translate well-defined marketplace questions into mathematical formulations, implement analyses and prototypes, design experiments, and interpret results using large-scale data.

  • Contribute to production systems through algorithm implementation,: validation, and monitoring, progressively taking ownership of well-scoped projects from initial hypothesis through measurable impact.

  • Operate in a fast-paced, constantly evolving environment where the ads: marketplace shifts quickly — you'll need to balance rigor with speed, and thrive when priorities change and new challenges emerge.

  • Communicate assumptions, findings, and limitations clearly to both technical: and cross-functional partners, helping the team make better decisions through transparency and analytical clarity.

  • PhD in mathematics, statistics, economics, operations research, or a related: quantitative discipline, with a strong foundation in at least one of the following areas: optimization, probability, statistical modeling, econometrics, or control theory.

What they're looking for

  • + years of software engineering experience, particularly in applying: quantitative methods to production systems.
  • Familiarity with ads systems, auction theory, or related marketplace optimization problems.
  • Experience working with large-scale data pipelines and real-time decision systems.
  • Familiarity with machine learning techniques and applying machine learning in production systems.