Amazon.com Services LLC
Financial Services
SeniorAppliedScientist
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Applied Scientist at Amazon.com Services LLC. Skills: Generative AI, Large language models, Machine learning, Applied research. Build AI systems for finance teams. Design agents that learn from user corrections”
Industry & Context.
Root cause analysis; Debugging; Data-driven decision making; Troubleshooting
What They're Looking For.
Must Have
Master's degree and 6+ years of applied research experience, 3+ years of building machine learning models for business application experience, Experience with neural deep learning methods, Experience programming in Java, C++, Python or related language
Nice to Have
PhD preferred, Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc., Experience with large scale distributed systems such as Hadoop, Spark etc.
What You'll Do.
Build AI systems for finance teams
Design agents that learn from user corrections
Solve inference at massive scale
Develop evaluation frameworks
Ship models to production
Measure customer workflow changes
How You'll Work.
Team & Collaboration
Cross-functional settings; Science, engineering, and business teams
Full Job Description
At Amazon's FinTech organization, we are building AI systems that process hundreds of millions of financial transactions, turn complex documents into actionable intelligence, and power autonomous agents that learn from every customer interaction. We are looking for a Senior Applied Scientist to lead the development of generative AI applications that change how finance teams work, tackling problems at the intersection of large language models, multi-agent systems, and real-world financial operations. Key job responsibilities What You'll Work On - Building AI systems that finance teams trust enough to rely on without manual review, where precision isn't a nice-to-have, it's a compliance requirement - Designing agents that learn from user corrections and get measurably better with every interaction, not just at the next model release - Solving inference at massive scale using tiered model architectures, intelligent routing, and small language models that deliver production-grade accuracy at a fraction of frontier model cost - Developing evaluation frameworks that catch quality regressions before customers do and gate every model change before it ships Who Thrives Here - You're someone who cares as much about shipping as about research. - You've built models that run in production, not just in notebooks. - You're comfortable working across the full stack, from model architecture to deployment to measuring whether the customer's workflow actually changed. - You operate well in cross-functional settings where science, engineering, and business teams inform each other continuously. - You'd rather solve a hard real-world problem than optimize a benchmark. What Makes This Different Your work ships to production and directly changes how thousands of finance professionals operate daily The problems are genuinely hard: financial data is messy, regulated, high-stakes, and operates at a scale where naive LLM approaches break down You'll work across multiple domains — from contrac
Applying for this Senior Applied Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about Amazon.com Services LLC?
Real rants from real employees. Read before you apply.