Software Development Engineer, Amazon Search ML - Berlin, Deutschland - Amazon TA

    Amazon TA
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    Beschreibung

    As an engineer on this growing ML team, you will take on akey role in helping us improve the customer experience of Amazon'sproduct search engine.

    We help customers find the products theyneed, by developing ML approaches that improve several componentsin the search experience.

    We are seeking a software engineer whowill assist us in deploying those models, integrating them intoexisting services, and optimizing theirperformance.


    This is a rewarding role whereyou will be able to draw a clear connection between your work andhow it improves the experience of millions of Amazon customersacross the globe every day.

    The team builds ML models trained onterabytes of product and traffic data, and you will play a criticalrole in building scalable, robust, and maintainable pipelinesneeded to train, evaluate, and deploy those models.

    The team is amixed science/engineering group, with each team member able tocontribute to both engineering excellence as well as scientificinnovation.

    Key jobresponsibilities

    • Design and implement newfeatures across the various software components powering our searchsystem
    • Participate in the design and deployment ofrobust and scalable pipelines for data processing, model training,and model inference
    • Build and configure metrics,dashboards, and alerting mechanisms for our deployed services andmodels

    Your will:

    • Work on ahighimpact, highvisibility product, with your contributionimproving the experience of millions of customers
    • Design and build pipelines that enable state of the art ML methodsto solve real world problems
    • Be a part of a growingteam where you can influence the team's mission, direction, and howwe achieve our goals
    • Publish (if desired) at internaland external scientific venues in the fields ofML/NLP/IR
    About theteam

    The Amazon Search organization owns the softwarethat powers product search — a critical customer-facing feature Whenever you visit an Amazon site, anywhere in theworld, our technology is what delivers you comprehensive searchresults at lightning speed.


    Within this largeorganization, our Berlin-based ML team designs, builds, and deploysuniversal ML models to improve the customer experience and thequality of returned search results.

    This ensures our customers aremore likely to find the products they are searching for. The teamis a mixed science/engineering group, which prioritizes work thathas high potential for innovation, customer impact, andcollaboration.

    We are open to hiringcandidates to work out of one of the followinglocations:

    Berlin, BE,DEU

    BASIC QUALIFICATIONS

    - Bachelor'sdegree in computer science or a related quantitativefield

    • 3+ years of professional software developmentexperience
    • 1+ year of experience in buildinglargescale pipelines for data processing and ML modeltraining/inference
    • Strong coding and problemsolvingskills in at least one modern programming language such as Python,Java, C++, etc.
    • A general understanding of essentialmachine learning concepts (with no expectation of indepth MLknowledge or research experience)

    PREFERREDQUALIFICATIONS

    - Master's degree in computer science or arelated quantitative field

    • Professional experience withthe AWS family of services (e.g. S3, DynamoDB, EMR,EC2)
    • Prior experience designing and implementinglargescale data pipelines and/or ML pipelines
    • Priorworking experience within a multidisciplinary team of scientistsand engineers
    • An understanding of, and interest in,search/retrieval engines
    Amazon is an equalopportunities employer. We believe passionately that employing adiverse workforce is central to our success. We make recruitingdecisions based on your experience and skills. We value yourpassion to discover, invent, simplify and build. Protecting yourprivacy and the security of your data is a longstanding toppriority for Amazon. Please consult our Privacy ) to know more about how wecollect, use and transfer the personal data of ourcandidates.

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