DESCRIPTION

Amazon’s Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. Our systems process billions of products to algorithmically find products not already sold on Amazon and programmatically add them to the Amazon catalog. We apply parallel processing, machine learning and deep learning algorithms to evaluate products and brands in order to identify and prioritize products and brands to be added to Amazon’s catalog. The datasets produced by our team are used by teams across Amazon to improve: product information, search and discoverability, pricing, and delivery experience. Our work involves building state-of-the-art Information Retrieval (IR) systems to mine the web and automatically create structured entities from un-structure/semi-structured data. We constantly stretch the boundaries of large scale distributed systems, Elastic Computing, Big Data, and SOA technologies to tackle challenges at Amazon’s global scale.

Come join us in our journey to make everything – and yes, we do mean *everything* – that anyone wants to buy, available on Amazon!

We are looking for SDEs with strong technical knowledge, established background in engineering large scale software systems, and passion for solving challenging problems. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from design to coding, testing, and deployment, to achieve results in a fast paced environment.

Key job responsibilities
Key job responsibilities
As a member of the team, in this role, you will

– Work with Sr.SDEs and Principal Engineers to drive the technical and architectural vision of SM systems responsible for generation of structured domain entities from structured/semi-structured data.
– Develop systems and extensible frameworks for complete lifecycle management of domain entities and inter-entity relationships
– Build scalable interface to process external data requests and fulfil them in an automated way.
– Solve complex problems in automated identity generation, web-to-Amazon namespace translation, and classification of products.
– Design and develop solutions for efficient storage and vending/search of products and related information.
– Utilize serverless and big data technologies to develop efficient algorithms that operate of large datasets.
– Lead and mentor junior engineers, and drive best practices around design, coding, testability, and security.

BASIC QUALIFICATIONS

– 3+ years of non-internship professional software development experience
– 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
– Experience programming with at least one software programming language
– Bachelor’s Degree in Computer Science, advanced degrees preferred.
– Experience building complex software systems that have been successfully delivered to customer.
– Deep technical expertise and hands-on architectural understanding of distributed and service-oriented architectures.
– Has delivered large-scale enterprise software systems or large scale online services.
– Solid programming skills in OO languages (Java/Scala/C++/Python etc) and a deep understanding of object oriented design.
– Advanced knowledge of data structures and at ease in optimizing algorithms.

PREFERRED QUALIFICATIONS

– 4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
– Master’s degree in computer science or equivalent
– A deep understanding of software development life cycle and a good track record of shipping software on time
– Experience in data mining, machine learning algorithms, rules engines, and workflow systems.
– Deep understanding of SOA with proven ability in building highly scalable and fault tolerant systems using Cloud computing technologies.
– Deep understanding of Map Reduce paradigm with experience in building solutions using Big Data technologies like Spark, Hive etc .
– Experience in developing efficient algorithms that operate on large datasets.
– Exposure to AWS technologies is a big plus.