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Amazon

Software Development Engineer (Level 5), Content Attribution Performance & Evalu

Amazon, Seattle, Washington, us, 98127

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Description

Are you excited by machine learning and LLMs? Do you want to scale machine learning in Prime Video? Do you want to accelerate the pace of scientific innovation in Prime Video? Then, this job may be what you have been looking for.

The Content Localization, Understanding, and Enhancement (CLUE) organization in Prime Video is looking for a strong SDE to join its Content Attribution Performance and Experimentation (CAPE) team. CAPE's owns two platforms:

AI Acceleration and ML Ops: Owns a platform that aims to raise the bar on performance measurement, governance, and model management through systematic, scientific solutions and to accelerate science model development and deployment through automation and by guiding our stakeholders on the use of the platform.

Causal Inference: Develops statistical techniques, frameworks, datasets, and software solutions for causal inference to inform prioritization decisions, evaluate the impact of our products post-launch, make systematic operational decisions, and implement feedback loops to improve our measurement and quality gating systems.

In 2025, CAPE will deliver on its mission through two projects PV ExAct (Causal Inference) and AI Builder Tools (AI Acceleration and ML Ops) by collaborating with teams in Prime Video's technology division, Central Product, and Prime Video's finance. As a platform team, we embed our solutions and services in the technology systems, operational processes, and investment-decision-making frameworks of teams through out Prime Video. As a result, this job gives you a unique opportunity to gain wide-ranging understanding of the video streaming business.

As an SDE in CAPE, you will work closely software engineers and scientists in Prime Video's digital supply chain. You will help advance our AI Builder Tools platform to accelerate and improve science-based solutions in Prime Video along the entire life cycle of ML applications: data set annotation, SOP management (including statistical protocols), model training (including LLMs), model performance measurement, model deployment to production, automated release of model updates to production, in-production performance measurement, orchestration of data pipelines and model chains, and systematic decision-making (e.g., detecting anomalies in customer engagement and triggering corrective operational actions.

As a member of CAPE, you will work as part of an integrated team of scientists and engineers, and the scientists in your team will be your stakeholders. The AI Builder Tools platform is how our scientists are deploying and scaling their causal inference solutions to the rest of Prime Video. This means that you will help introduce state-of-the art statistical methods and protocols to help Prime Video to make scientifically rigorous investment and operational decisions.

Other reasons to join this team:

Being part of a team that is at the heart of state-of-the-art ML engineering and causal inference

Working at the intersection of science and engineering to inject systematic, scientific decision making into Prime Video's decision making

Closely collaborating with some of the brightest software engineers and scientists solving state-of-the-art ML engineering problems and launching products that will have a major impact on Amazon-internal teams and Prime Video's streaming customers.

Being part of a team that values creativity and welcomes outside-of-the-box thinking (thinking big!).

Being part of a team with a high emphasis on a positive work culture of collaboration.

Being part of a team whose manager cares deeply about talent development

Basic Qualifications

3+ years of non-internship professional software development experience

2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Experience programming with at least one software programming language

Preferred Qualifications

3+ 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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.