Interested in building something new? Join the Amazon Autos team on an exhilarating journey to redefine the vehicle shopping experience.
This is an opportunity to be part of the Amazon's new business ventures. Our goal is to create innovative automotive discovery and shopping experiences on Amazon, providing customers with greater convenience and a wider selection.
You'll work in a creative, fast-paced, and entrepreneurial environment at the center of Amazon's innovation. As a key member, you'll play a pivotal role in helping us achieve our mission. We are looking for a highly accomplished Applied Science professional drive our science strategy, foster a culture of data-driven decision-making, and drive impactful business outcomes through advanced state-of-the-art science methodologies.
If you're enthusiastic about innovating and delivering exceptional shopping experiences to customers, thrive on new challenges, and excel at solving complex problems using top-notch ML models, LLM and GenAI techniques, then you're the perfect candidate for this role. Strong business acumen and interpersonal skills are a must, as you'll work closely with business owners to understand customer needs and design scalable solutions.
Join us on this exhilarating journey and be part of redefining the vehicle shopping experience.
Key job responsibilities
As an Applied Scientist in Amazon Autos, you will:
- Shape the roadmap and strategy for applying science to solve customer problems in the Amazon AutoStore domain.
- Drive big picture innovations with clear roadmaps for intermediate delivery.
- Apply your skills in areas such as deep learning and reinforcement learning while building scalable solutions for business problems.
- Produce and deliver models that help build best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput.
- Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation.
- Interface with business customers, gathering requirements and delivering science solutions.
- Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.
- Effectively communicate complicated machine learning concepts to multiple partners.
- Research new and innovative machine learning approaches.
A day in the life
In this role, you will be part of a multidisciplinary team working on one of Amazon's newest business ventures. As a key member, you will collaborate closely with engineering, product, design, operations, and business development to bring innovative solutions to customers.
Your science expertise will be leveraged to research and deliver novel solutions to existing problems, explore emerging problem spaces, and create new knowledge. You'll invent and apply state-of-the-art technologies, such as large language models, machine learning, NLP, and computer vision, to build next-generation solutions for Amazon.
You'll publish papers, file patents, and work closely with engineers to bring your ideas to production.
About the team
This is a critical role for Amazon Autos team with a vision to create innovative automotive discovery and shopping experiences on Amazon, providing customers better convenience and more selection. We’re collaborating with other experienced teams at Amazon to define the future of how customers research and shop for cars online.- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Master's degree or above in computer science, machine learning, engineering, or related fields- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
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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.
