Sr. Software Development Mgr, SPS Machine Learning Accelerator
Amazon.com
Are you interested in being part of a fast-paced technology company with the largest e-commerce platform in the world, and build scalable AI systems that protect customers to earn their trust? You will be building scalable systems that use Machine Learning (ML) to continuously learn and prevent malicious actors, and preserve customer trust. You will have the opportunity to solve the toughest technical problems in the industry and develop powerful tools, which enable rapid business growth.
Group Overview
Selling Partner Services (SPS) is the organization that constantly makes high-judgment decisions across a wide breadth of constituents. We build and deliver services for Buyers, Sellers, Vendors and other customers. We ensure that Amazon is a safe and trustworthy place to shop and an amazing place for software developers to help building a successful business, selling products. We support our many partners in this journey. We face constant trade-offs and competing objectives that we need to appropriately balance. We have to do all of this at high scale, which only happens through technology and science. We are a large organization that leads innovation in many areas, so we also play a critical role in helping Amazon more broadly beyond our own goals.
We’re the SPS Machine Learning Accelerator (MLA) team, a team of senior scientists and software engineers, focusing on inventing, prototyping and proving out new and advanced ML techniques that solve fundamentally hard problems and provide step-function improvements over a multi-year period to the SPS mission and goals. These technical innovations are deeply rooted in business needs and require close collaboration with both technical communities within SPS, and SPS business leaders alike. The SPS MLA team spearheads technological advancement, and demonstrates its effectiveness in production, while also acting as a center of excellence for ML practices within SPS.
We create next-generation solutions that help accelerate AI and ML development and business deployment, with end-to-end, scalable, highly-automated and intelligent ML model building and ML feature engineering solutions. We not only leverage industry leading AI technology such as AWS AI, open-source AI framework, we innovate our own solutions that are ahead of the curve.
Key Responsibilities
You will be a technical leader on your team, working closely with software engineers and ML scientists. You will work efficiently and routinely to deliver the right projects with limited guidance. You will have the autonomy to drive technical breakthroughs and influence the broad SPS tech community, with strong support from tech and business leaders. Your work focuses on ambiguous problem areas to create next-generation ML-rooted solutions to delight customers and stop bad actors.
1. Take ownership of team architecture, providing a system-wide view and design guidance.
2. Split work into parallel tasks that can be performed by you and others and then reassembled successfully.
3. Provide context for current technology choices and guide future technology choices.
4. Influence software decisions made by other teams.
5. Make right technical trade-offs between short-term technology or operational needs and long-term business needs.
6. Actively recruit and help others leverage your expertise, by coaching and mentoring in your organization.
Group Overview
Selling Partner Services (SPS) is the organization that constantly makes high-judgment decisions across a wide breadth of constituents. We build and deliver services for Buyers, Sellers, Vendors and other customers. We ensure that Amazon is a safe and trustworthy place to shop and an amazing place for software developers to help building a successful business, selling products. We support our many partners in this journey. We face constant trade-offs and competing objectives that we need to appropriately balance. We have to do all of this at high scale, which only happens through technology and science. We are a large organization that leads innovation in many areas, so we also play a critical role in helping Amazon more broadly beyond our own goals.
We’re the SPS Machine Learning Accelerator (MLA) team, a team of senior scientists and software engineers, focusing on inventing, prototyping and proving out new and advanced ML techniques that solve fundamentally hard problems and provide step-function improvements over a multi-year period to the SPS mission and goals. These technical innovations are deeply rooted in business needs and require close collaboration with both technical communities within SPS, and SPS business leaders alike. The SPS MLA team spearheads technological advancement, and demonstrates its effectiveness in production, while also acting as a center of excellence for ML practices within SPS.
We create next-generation solutions that help accelerate AI and ML development and business deployment, with end-to-end, scalable, highly-automated and intelligent ML model building and ML feature engineering solutions. We not only leverage industry leading AI technology such as AWS AI, open-source AI framework, we innovate our own solutions that are ahead of the curve.
Key Responsibilities
You will be a technical leader on your team, working closely with software engineers and ML scientists. You will work efficiently and routinely to deliver the right projects with limited guidance. You will have the autonomy to drive technical breakthroughs and influence the broad SPS tech community, with strong support from tech and business leaders. Your work focuses on ambiguous problem areas to create next-generation ML-rooted solutions to delight customers and stop bad actors.
1. Take ownership of team architecture, providing a system-wide view and design guidance.
2. Split work into parallel tasks that can be performed by you and others and then reassembled successfully.
3. Provide context for current technology choices and guide future technology choices.
4. Influence software decisions made by other teams.
5. Make right technical trade-offs between short-term technology or operational needs and long-term business needs.
6. Actively recruit and help others leverage your expertise, by coaching and mentoring in your organization.
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