About The Position

The Ads Performance Measurement team within Amazon Ads' Measurement, AdTech, and Data Science (MADS) organization serves a centralized role developing solutions for a multitude of performance measurement products to measure the full impact of advertiser spend, including both online and offline sales impacts across all timeframes. It delivers actionable insights for advertisers to optimize media portfolios. We build advanced ads measurement solutions using AI/ML that enable advertisers to go beyond traditional media KPIs and begin optimizing marketing strategies towards their ultimate business goals like long-term sales and customer loyalty. We leverage new technologies including Generative AI, machine learning, causal inference, natural Language Processing (NLP), and Computer Vision (CV) to drive these innovations. As a Tech lead on the team, you will lead the engineering work-stream of building a new Amazon ads foundational model that enables advertisers to optimize directly for business outcomes through AI-powered understanding of complete customer journeys. You will define the technical vision to streamline the model development lifecycle from research to production, building ML infrastructure and establishing MLOps practices that enables rapid experimentation and deployment of ML models. You will invent and design new solutions to solve complex challenges that come with petabyte scale storage.

Requirements

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution

Nice To Haves

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

Responsibilities

  • Directly contribute to the end-to-end delivery of production solutions through careful designs and owning implementation of significant portions of critical-path code
  • Create robust, scalable ML infrastructure and data pipelines
  • Own & improve deployment, testing, configuration management, and monitoring practices for ML infrastructure
  • Build model-serving frameworks optimized for production environments, supporting real-time and batch execution.
  • Collaborate with Applied Scientists, Economists, Product Managers, and Senior technical leaders to align technical solutions with strategic objectives
  • Mentor junior engineers and contribute to technical knowledge sharing
  • Lead technical design reviews and provide architectural guidance
  • Establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.
  • Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives
  • Foster collaborations among scientists and engineers to move fast and broaden impact
  • Actively engage in the development of others, both within and outside of the team
  • Set an example for others with exemplary analyses; maintainable, extensible code; and simple, effective solutions

Benefits

  • health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
  • 401(k) matching
  • paid time off
  • parental leave
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