Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience?
Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and create solutions that have cross-organizational impacts?
If yes, then you may be a great fit to join the Machine Learning Accelerator team.
Key job responsibilities
The scope of an Applied Scientist in the Machine Learning Accelerator (MLA) team is to research and prototype AI and Machine Learning applications that solve strategic business problems across Selling Partner Experience (SPX) domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale that are of broad benefit to SPX organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team's technical strategy by making insightful contributions to the team's priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building machine learning models or developing algorithms for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with LLM fine-tuning, in-context learning, or model evaluation
- Hands-on experience designing reward models or RL post-training pipelines (PPO/GRPO, DPO) for LLMs or agents, including preference-data collection and evaluation
- Experience building agentic AI systems - tool use, planning, retrieval-augmented generation, or multi-agent workflows
- Experience with researching and developing neuro-symbolic solutions and applications
- Publications at top ML/AI venues
- Experience partnering with product/engineering teams to deliver ML in large-scale production system
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, CA, San Diego - 142,800.00 - 193,200.00 USD annually
