Want to work for a fast-paced, innovative team? Want to work on ground-breaking initiatives? Want to work on problems that have massive scale but also need high precision? We are seeking a strong data science leader for our Workforce Staffing organization.
Workforce Staffing is responsible for hiring hourly associates into our global fulfillment operation. Each year we hire over 1 million associates across the globe. Workforce Intelligence (WFI), a subsidiary of Workforce Staffing (WFS), is responsible for driving decisions that help Workforce Staffing deliver the scale and precision it needs while minimizing the cost of hiring. WFI manages data acquisition, engineering, research, science and products that help WFS make the best decisions. Hiring over 1 million associates around the world presents the largest staffing challenge in a private company environment. The complexity is high and precision is needed because over hiring leads to unnecessary increase in wage and under hiring leads to delayed delivery of products to Amazon’s customers. There are over a dozen levers that WFS can pull to manage the scale and precision of hiring.
Key job responsibilities
As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge, technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of a MLOPS automation framework via collaboration with the engineering and research communities.
You will collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems and you will provide support for business continuity on a rotating on call.
A day in the life
Almost everyday offers new challenges and opportunities for growth. Where one day will offer implementation of Self-Service MLOps tooling, the next day may be focused on our operational excellence in maintaining our code base. Later in the week, you may sort technical challenges with our partners to help them enrich their products with our models. On some days or weeks, you may watch over our products and stand ready to intervene and provide support to partners consuming our models.
About the team
We work back to back to address the technical challenges of automation across a variety of products, software, and systems. Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each other's skills. Together, we are a powerful team of global specialists bringing the potential of practical ML and AI to the max with impact on over a million of candidates applying for a Job in Amazon.
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 3+ years experience and knowledge in MLOps, in deploying, operationalizing, and maintaining scalable AI/ML-solutions in production
- 1+ 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
- Bachelor's degree in computer science or equivalent
PREFERRED QUALIFICATIONS
- 2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Master's degree in computer science or equivalent
- Experience in machine learning, data mining, information retrieval and statistics.
