Amazon.com Services LLC
Applied Science, consumer engagement
SeniorAppliedScientist,C360
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Applied Scientist, C360 at Amazon.com Services LLC. Skills: Large Language Models, Machine Learning, Information Retrieval, Personalization. Own scientific roadmap. Identify research directions”
What You'll Achieve.
Improve core capabilities
Industry & Context.
Translate ambiguous business problems; Solve real-world problems
What They're Looking For.
Must Have
4+ years applied research, 3+ years ML models business application, Master's degree 6+ years applied research, Programming in Java, C++, Python, Experience neural deep learning, Experience machine learning
Nice to Have
Modeling tools experience, Large scale distributed systems experience
What You'll Do.
Own scientific roadmap
Identify research directions
Translate business problems
Design end-to-end systems
Run offline experimentation
Drive production A/B testing
Drive technical decisions
Balance scientific rigor
Balance business impact
Balance operational constraints
Raise bar for science team
Establish best practices
Influence cross-functional strategy
Partner with engineering
Partner with leadership
Define product vision
Publish state of the art
Advance state of the art
Contribute to ML community
Generate opportunities
Develop statistical models
Innovate on behalf of customer
Build features strategically
Mentor junior members
Help junior members grow
How You'll Work.
Team & Collaboration
Partnering with engineering; Partnering with product; Partnering with leadership; Collaboration with other Scientists; Collaboration with Engineers; Collaboration with Product Managers
Communication Scope
Clear communication
Process & Methodology
Roadmap planning
Full Job Description
Are you a scientist passionate about advancing Information Retrieval, NLP, and Large Language Models? Do you want access to massive datasets, world-class compute, and a team of top scientists and engineers building the future of e-commerce? If so, you'll be a great fit for our team at Amazon. 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
Applying for this Senior Applied Scientist, C360 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.