Amazon.com Services LLC
Technology
Sr.SoftwareDevelopmentEngineer,AmazonRoboticsManipulation
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“Sr. Software Development Engineer, Amazon Robotics Manipulation at Amazon.com Services LLC. Skills: Software development, System design, Cloud computing. Design, develop, test, deploy, maintain, and improve software. Manage individual projects”
What You'll Achieve.
Deliver high-quality software; Meet project deadlines; Contribute to team success
Industry & Context.
Root cause analysis; Troubleshooting; Analytical thinking
What They're Looking For.
Must Have
Bachelor's degree or equivalent practical experience, 5+ years of experience in software development, Experience with at least one general-purpose programming language
Nice to Have
Master's degree or PhD in Computer Science or related field, Experience with distributed systems, Experience with cloud computing platforms (AWS, Azure, GCP), Experience with machine learning or artificial intelligence
What You'll Do.
Manage individual projects
Identify and resolve issues
Mentor junior engineers
Contribute to team and customer goals
How You'll Work.
Team & Collaboration
Cross-functional teams; Agile development
Communication Scope
Technical documentation; Verbal communication
Process & Methodology
Agile, Scrum
Full Job Description
The Fleet Performance Optimization (FPO) organization builds the intelligence layer for Amazon Robotics manipulation workcells. We own the systems that select what work a robot should attempt, monitor how it performs, and close the loop by improving models with every induct. Our platforms serve Sparrow, Cardinal, FlexCell, and Robin workcells that handle millions of packages across Amazon's fulfillment network. We operate across the full ML and data lifecycle: Work Selection Intelligence — Eligibility scoring and predictions (likelihood-to-empty, damage prediction, time-to-process, pick eligibility) that feed into work planners, determining which totes and items reach each workcell. Data & Observability — A common datalake collecting telemetry from every automated and manual workcell, fleet monitoring that detects performance degradation in real time and alerts Ops, and deep-dive tooling that enables engineers and scientists to investigate workcell behavior. ML Lifecycle — Annotation orchestration, model training pipelines, production monitoring, and deployment infrastructure that keeps models current across the fleet. Predictive Models — Science-developed foundational models applied to eligibility, fleet performance forecasting, and dynamic floor policies that adapt to changing conditions without manual intervention. Our systems process tens of millions of events daily, serve real-time scoring at workcell-runtime latency, and directly impact fulfillment cost per unit. Key job responsibilities As an SDE on FPO, you will design, build, and operate distributed systems that sit at the intersection of robotics, machine learning, and large-scale data processing. You will work closely with scientists, program leads, and partner engineering teams to translate research into production systems that operate reliably at fleet scale. Depending on the team, your work may include: - Building high-throughput, event-based scoring services that process real-time inventory signals ac
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