Thinking Machines LabRemote · San Francisco$350k-$475k4h ago
AmazonPosted 3mo ago
Sr. Applied Scientist, C360 at Amazon scores 98 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.
AI in this role
We build large-scale ML solutions that deliver personalized, up-to-date recommendations to millions of customers. Our team is uniquely positioned to shape how customers think about their shopping journey.
We're looking for scientists with deep LLM expertise to build our next generation of models. The team focuses on post-training—instruction tuning, reward modeling, reinforcement learning, and multi-modal alignment. You'll design and run large-scale experiments, analyze model behavior, and develop training recipes that improve core capabilities like reasoning, personalization, and other frontier paradigms.
Key job responsibilities
- Own the scientific roadmap for personalization initiatives, identifying high-impact research directions and translating ambiguous business problems into well-defined ML formulations
- Design and lead end-to-end systems spanning recommendations, information retrieval, and LLM fine-tuning, from problem framing through offline experimentation to production A/B testing and launch
- Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact and operational constraints
- Mentor and raise the bar for the science team through design reviews, paper discussions, and establishing best practices for experimentation and reproducibility
- Influence cross-functional strategy by partnering with engineering, product, and leadership to define the product vision informed by what's technically feasible and scientifically novel
- Publish and advance the state of the art — contribute to the broader ML community through patents, publications, and external engagement at conferences
A day in the life
You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, execute experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the organization. You get to influence stakeholders with clear communication skills. You innovate on behalf of the customer and strategically build features. You will mentor junior members and help them grow.
About the team
The team values innovations and offers a safe place to try, fail and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. Our team offers creative space with entrepreneurial work environment focusing on customer obsession.
Basic qualifications
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred qualifications
- 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.
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, Seattle - 167,100.00 - 226,100.00 USD annually
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
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 TensorFlow that you've run into, and how did you work around them?
- What's a project where you used scikit-learn hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Fine Tuning, Nlp, 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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