# Machine Learning Engineer, AWS Analytics Engineering Source: https://realanalystjobs.com/job/machine-learning-engineer-aws-analytics-engineering-amazon-3d3815d6 Machine Learning Engineer, AWS Analytics Engineering at Amazon, an on-site role based in Seattle, Washington, USA. Experience level: 3+ Years. Posted on 18 September 2026, read from Amazon's own careers page (Amazon), which RealAnalystJobs re-checks daily and removes the role when it closes. Amazon has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Amazon](https://realanalystjobs.com/companies/amazon) - Location: Seattle, Washington, USA - Work mode: On-site - Posted: Sep 18, 2026 - Employment type: Full time - Experience level: 3+ Years - Source: Amazon's careers page (Amazon), re-checked daily Skills: AWS ## Visa sponsorship The posting does not say. Amazon had H-1B petitions approved for 12,010 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/amazon#h1b-record) ## About this role 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. 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 - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and p Description from Amazon's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/machine-learning-engineer-aws-analytics-engineering-amazon-3d3815d6) and use Apply now there to reach the employer's application. The listing is re-checked against Amazon's careers page daily and removed when it closes. ## Amazon 583 open analyst roles on Real Analyst Jobs. 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