At Amazon Search, we power the discovery experience that connects millions of customers to the products they seek across our global marketplace. Our team develops sophisticated search solutions that make Amazon's vast product catalog easily accessible to customers worldwide. We're building next-generation search infrastructure that enables seamless expansion into new markets and product categories. Our mission is to ensure every customer enjoys an exceptional search experience from day one, whether they're shopping in an established market or a newly launched region.
We develop intelligent, scalable systems that optimize search quality and effectiveness across Amazon's diverse product ecosystem. Our innovations help customers find exactly what they're looking for, while enabling Amazon to rapidly expand its global presence with consistent, high-quality search capabilities. We are seeking a strong applied scientists to join the newly formed Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models.
Key job responsibilities
Key job responsibilities
* Build machine learning models for Product Search.
* Develop new ranking features and techniques building upon the latest results from the academic research community.
* Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system.
* Focus on identifying and solving customer problems with simple and elegant solutions.
* Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.
* Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems.
* Take ownership. Understand the needs of various search teams, distill those into coherent projects, and implement them with an eye on long-term impact.
* Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects.
* Be ambitious. Find and eagerly tackle hard problems.
* Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the cutting-edge technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively.
* Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 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 large scale distributed systems such as Hadoop, Spark etc.
- Strong fundamentals on a broad set of ML approaches and techniques
- Strong fundamentals in problem solving and algorithm design
- Strong interest in learning, researching, and creating new technologies with commercial impact
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit 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.