About the position
We are seeking a Senior Applied Scientist to build production machine learning\nsystems that solve complex business problems at scale. You will design, develop,\nand deploy ML solutions that directly impact millions of users and drive\nstrategic decision-making across the organization.\n\nIn this role, you will work on challenging problems spanning predictive\nmodeling, natural language processing, recommendation systems, and generative AI\napplications. You will collaborate with cross-functional teams to translate\nambiguous business challenges into rigorous technical solutions.\n\nThe People eXperience and Technology Central Science Team (PXTCS) uses\neconomics, behavioral science, statistics, and machine learning to proactively\nidentify mechanisms and process improvements which simultaneously improve Amazon\nand the lives, wellbeing, and the value of work to Amazonians. We are an\ninterdisciplinary team that combines the talents of science and engineering to\ndevelop and deliver solutions that measurably achieve this goal.
Responsibilities
- Design and deploy large-scale machine learning systems in production environments
- Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI
- Create ML solutions that standardize and optimize manager-employee interactions, providing intelligent suggestions and establishing metrics to measure engagement quality across diverse conversation types
- Partner to build causal inference models and experimental frameworks to measure impact
- Collaborate with product managers, engineers, and business leaders to define technical roadmaps
- Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership
Requirements
- PhD, 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
Nice-to-haves
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Proven track record of leading end-to-end development from Ideation to monitoring in production
- Proven track record of mentoring and growing junior and mid-level scientists
- Experience with building LLMs, generative AI applications on AWS
- Excellent communication skills with ability to influence senior leadership
- Demonstrated ability to work in ambiguous problem spaces with evolving requirements
Benefits
- 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
- parental leave