The Private Brands Discovery team designs innovative machine learning solutions to enhance customer awareness of Amazons own brands and help customers find products they love. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using cuttingedge technology to tackle some of the most challenging scientific problems at Amazon. To achieve this the team utilizes methods from Natural Language Processing deep learning large language models (LLMs) multiarmed bandits reinforcement learning Bayesian optimization causal and statistical inference and econometrics to drive discovery throughout the customer journey. Our solutions are crucial to the success of Amazons private brands and serve as a model for discovery solutions across the company.
This role presents a highvisibility opportunity for someone eager to make a business impact delve into largescale problems drive measurable actions and collaborate closely with scientists and engineers. As a team lead you will be responsible for developing and coaching talent guiding the team in designing and developing cuttingedge models and working with business marketing and software teams to address key challenges. These challenges include building and improving models for sourcing relevance and CTR/CVR estimation deploying reinforcement learning methods in production etc.
In this role you will be a technical leader in applied science research with substantial scope impact and visibility. A successful team lead will be an analytical problem solver who enjoys exploring data leading problemsolving efforts guiding the development of new frameworks and engaging in investigations and algorithm development. You should be capable of effectively interfacing between technical teams and business stakeholders pushing the boundaries of what is scientifically possible and maintaining a sharp focus on measurable customer and business impact. Additionally you will mentor and guide scientists to enhance the teams talent and expand the impact of your work.
3 years of scientists or machine learning engineers management experience
Knowledge of ML NLP Information Retrieval and Analytics
Expert in developing largescale ML systems in a production environment
Extensive experience applying theoretical models in an applied environment
Demonstrated proficiency in deep learning models experience building production level causal inference models
Expert in more than one more major programming / scripting languages (Python Scala PySpark or similar)
Excellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience.
Experience coaching and reviewing work of junior ML Scientists making great hiring decisions.
Experience building machine learning models or developing algorithms for business application
Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers
Experience building machine learning models or developing algorithms for business application
Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers
Team building and science recruiting experience
Comprehension of tech stacks and could stay on top of tactical
Strong doc writing skills
Strong fundamentals in problem solving algorithm design and complexity analysis
Proven track record of delivering ML models in production
External Publications
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165500/year in our lowest geographic market up to $286000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.