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Benefits & Perks
•Healthcare
•401(k)
•Equity
•Parental Leave
•Mental Health
•Healthcare
•401k
•Equity
•Parental Leave
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Required Skills
Software development
Machine Learning
Large Language Models
System design
Architecture design
Team leadership
The Ads Performance Measurement team within Amazon Ads' Measurement, Ad Tech, 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.
- Key job 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
Basic Qualifications
- 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
Preferred Qualifications
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 184,900.00 - 250,200.00 USD annually
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
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Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L4
0 reports
$181,968
total / year
Base
-
Stock
-
Bonus
-
$154,672
$209,264
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
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