AmazonPosted 1mo ago

Senior Applied Scientist, APEX

Senior Applied Scientist, APEX at Amazon scores 100 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Bellevueseniorfull-time$167k-$226k

AI in this role

pytorchtensorflowscikit-learn

fine-tuningnlp

Alexa AI is looking for a Senior Applied Scientist to build Alexa+, Amazon's LLM-powered conversational assistant. You will work on key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide.

As a Senior Applied Scientist, you are a strong technical contributor who independently drives complex projects from ideation to production. You design and run rigorous experiments, develop novel approaches to challenging problems, and deliver high-quality models and systems at scale. Your work is characterized by scientific rigor, engineering excellence, and a focus on measurable customer impact.

You collaborate effectively across teams, contribute to scientific discussions and reviews, and help elevate the technical bar within the organization. You proactively identify opportunities, propose solutions, and influence technical direction within your project area.

Basic Qualifications
- PhD/MS in Computer Science, Electrical Engineering, Machine Learning, Natural Language Processing, or a related technical field, OR Master's degree with 5+ years of relevant industry experience
- 3+ years of hands-on experience in applied machine learning, predictive modeling, or NLP
- Strong programming skills in Python or a related language
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
- Track record of delivering ML/NLP solutions from research to production
- Experience working with large language models (training, fine-tuning, or evaluation)

Preferred Qualifications
- 5+ years of relevant industry or academic research experience
- Experience with LLM alignment techniques (RLHF, DPO, constitutional AI)
- Experience with agentic AI systems, including planning, tool use, and orchestration
- Experience with distributed training and large-scale model optimization
- Peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, ICLR)
- Strong communication skills with the ability to present complex technical concepts to diverse audiences
- Experience mentoring junior scientists or engineers

Key job responsibilities
- Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment
- Develop and improve agentic systems — including multi-step reasoning, tool use, planning, and orchestration — that work reliably at scale
- Build evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality
- Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams
- Analyze large-scale experimental results, identify patterns, and iterate rapidly on model improvements
- Publish results at top-tier venues and contribute to Amazon's presence in the broader research community
- Mentor junior scientists and contribute to hiring efforts

About the team
Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning from human feedback and verifiable rewards, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.

Basic qualifications

- PhD or equivalent research experience, or Master's degree and 5+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Track record of delivering ML/NLP solutions from research to production
- Experience working with large language models (training, fine-tuning, or evaluation)
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- 5+ years of industry or academic research experience
- Experience with training and deploying machine learning systems to solve large-scale optimizations
- Experience communicating complex ideas to technical and non-technical audiences
- Experience with LLM alignment techniques (RLHF, DPO, constitutional AI)
- Experience with agentic AI systems, including planning, tool use, and orchestration
- Peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, ICLR)

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 parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually

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Skills and AI tools this role asks for

Fine TuningNlpPyTorchTensorFlowscikit-learn

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
What NLP problem have you worked on, and how did you measure whether it actually worked?
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.

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List these exact terms on your resume: Fine Tuning, Nlp, PyTorch, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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