We are seeking a Machine Learning Engineer to join our team and drive the next generation of our data platform and AI powered products at AWS scale. You will own end to end design, implementation, and operation of distributed systems that process petabyte scale data daily, serve hundreds of internal customers, and directly influence how AWS leadership makes decisions.
This is a high impact role where you will shape the architecture of both products, building workflow orchestration systems, multi agent AI frameworks, GenAI powered analytics capabilities, and scalable platform services. You will operate at the intersection of distributed systems, data engineering, and applied AI/ML.
Key job responsibilities
Own and evolve system architecture. Design and implement scalable, secure, and cost effective distributed systems for workflow orchestration and AI powered analytics. Make sound technical trade offs between short term delivery and long term maintainability.
Drive architectural decisions that impact petabyte scale data processing and thousands of jobs.
Build multi agent AI systems. Design, implement, and optimize multi agent architectures including autonomous agents, orchestration frameworks, and tool integrations
Build reusable components, APIs, and micro-services that other teams adopt. Continuously simplify, optimize, and remove bottlenecks across the stack.
Drive platform capabilities end to end. Own features from concept through deployment and operation. Examples include building new marketplace and IDE experiences, implementing validated query patterns, designing cross service governed metrics, or creating real time monitoring dashboards.
Solve complex ambiguous problems. Navigate unclear requirements and competing priorities to deliver innovative solutions.
Influence technical direction and mentor others. Provide technical leadership across the team and adjacent teams.
Drive operational excellence. Own the operational health of production systems.
Innovate with AI/ML technologies. Stay current with GenAI, LLM, and ML advancements.
A day in the life
As a Senior Software Development Engineer, you will work closely with your customers and stakeholders to understand their analytics needs, translating them into scalable technical solutions on our data platform. You will work with cross functional teams including data engineers, applied scientists, product managers, and business analysts. You will design and build distributed systems that orchestrate thousands of daily workflows and process petabyte scale data across AWS services. ou will spend time writing and reviewing code, diving deep into production issues, and mentoring engineers on best practices. You will participate in architecture design and review meetings to hold a high standard for our infrastructure. You will balance building new capabilities with operational excellence, ensuring our systems are reliable, secure, and performant at scale.
About the team
The AWS Analytics Engineering (AAE) organization is the analytics backbone of AWS. We build and operate the data platform that powers business decisions across all of AWS services. Every insight surfaced to AWS product leadership, from service adoption trends to revenue drivers, flows through systems our team designs, builds, and maintains.
We are a team of engineers and scientists supporting AWS product leaders to make high impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We came from diverse backgrounds from statistics, computer science, engineering, and business analytics. We specialize in building data platforms that process at petabyte scale and the full end to end ML development process, from data ingestion to model deployment in production.