Entra a far parte del team di NIKE, Inc.

NIKE, Inc. è molto più di un brand che veste e attrezza gli atleti e le atlete migliori al mondo: è un luogo in cui persone appassionate si incontrano per creare il futuro dello sport. Sappiamo bene chi siamo e cosa vogliamo: portare innovazione e ispirazione a ogni atleta* nel mondo. Cerchiamo Athlete capaci di alzare l'asticella, esprimere al massimo il nostro potenziale e guidarci verso l'eccellenza. Una generazione pronta a dettare i trend e le regole del gioco, ad assumersi rischi e a creare spirito di squadra. Ti riconosci?

WHO YOU WILL WORK WITH

You will work closely with business stakeholders, product owners, and your peers within the engineering team to ensure the successful delivery of solutions. Additionally, you will work with other technology teams that lead the up and down-streams solutions to coordinate dependencies. 

WHO WE ARE LOOKING FOR

We seek passionate engineers to join our team. As a Lead AI/ML Engineer, you will influence and develop robust machine learning and generative AI solutions that have a direct impact on the business. You should have experience in Python; a strong background in algorithms and data structures; hands-on AWS experience; as well as experience in database technology (e.g. Postgres, Redis) and data processing technology (e.g. SageMaker or Databricks). You should also have a demonstrable history of team leadership and value delivery, and be comfortable working in an agile product model.

As a Lead AI/ML Engineer, you will be expected to own projects end-to-end - from conception to operationalization - demonstrating a command of the full software development lifecycle. You will set the technical direction for your team, provide vision and guidance to your teammates, and raise the bar on engineering quality; therefore, strong communication and leadership skills are critical in this role.

WHAT YOU WILL WORK ON

If this is you, you’ll be working with the Corporate Functions Artificial Intelligence team at Nike focused on delivering AI capabilities for Nike’s corporate functions. With teammates globally distributed, you’ll be joining a global organization working to solve machine learning problems at scale. You’ll be designing and implementing scalable applications that leverage prediction models and optimization programs to deliver data driven decisions that result in immense business impact. You’ll also contribute to core advanced analytics, machine learning, and generative AI platforms and tools to enable both prediction and optimization model development. You thrive when surrounded by talented colleagues and aim to never stop learning. We are looking for candidates who enjoy a collaborative and academic environment where we develop and share new skills, mentor, and contribute knowledge and software back to the analytics and engineering communities both within Nike and at-large.

WHAT YOU BRING

To make it clear, we're not looking for just anyone. We're looking for someone special, someone who had these experiences and clearly demonstrated these skills:

  • Undergraduate degree in Computer Science, a Master's degree in a related engineering field, or equivalent experience

  • 8+ years of professional experience in software engineering

  • 3+ years of experience in the field of Machine Learning Engineering or related fields

  • A demonstrable history of technical leadership, mentoring engineers, and delivering value in an agile product model

  • Strong analytical mindset and experience leading others in problem solving

  • Proficiency working in a team and mentoring others to write robust, maintainable, and extendable code in Python; containerized in Docker, and automated with CI/CD

  • Expertise with agile development and test-driven development

  • Expertise with data structures, data modeling and software architecture

  • Expertise in producing predictive or mathematical optimization models and deploying them to production

  • Expertise in MLOps and an ability to articulate the role of MLOps in the machine learning development lifecycle from experimentation to production and measurement

  • Familiarity with frameworks such as Scikit-learn, PyTorch, TensorFlow, Spark, FastAPI or similar platforms and frameworks

  • Experience with complex data sets, ETL pipelines, SQL, and general data engineering

  • Expertise with cloud architecture and technologies, especially Amazon Web Services: ECR, SageMaker, Lambda, API Gateway

  • Familiarity with pipeline orchestration tools such as Airflow or Databricks Workflows

  • Experience with database technology (e.g. Postgres, Redis) and data processing technology (e.g. SageMaker or Databricks)

  • Expertise with Spark, Kubernetes, Docker, Jenkins, Databricks, or Terraform is highly desirable

  • Effective communication skills with team members, stakeholders, the business, and in code

  • Experience influencing technical strategy through all aspects of technical design and implementation

  • Proficiency providing technical leadership within a team and mentorship to others

    Una breve introduzione

    IL NOSTRO PIANO DI ASSUNZIONE

    01 Candidati

    I nostri team sono composti da persone che apportano un'ampia varietà di competenze, conoscenze, input, idee e background. Vogliamo aiutarti a trovare il tuo posto: rivedi le descrizioni delle posizioni, i reparti e i team per trovare il ruolo adatto a te.

    02 Incontra un/una recruiter o completa una valutazione

    Se selezionato per un ruolo aziendale, un reclutatore ti contatterà per avviare il processo di colloquio e sarà il tuo contatto principale durante tutto il processo. Per i ruoli di vendita al dettaglio, completerai una valutazione interattiva che include una chat e quiz e richiederà circa 10-20 minuti per essere completata.  Indipendentemente dal ruolo, vogliamo conoscere te, la tua totalità, quindi non esitare a scoprire il modo in cui ti avvicini a un servizio di livello mondiale e ciò che ti rende unico.

    03 Preparati per il colloquio

    Affronta questa fase con sicurezza, facendo le tue ricerche, comprendendo cosa stiamo cercando e preparandoti a rispondere alle domande che sono state ideate per saperne di più su di te e sul tuo background.

    Due persone che sorridono e si abbracciano in un ambiente esterno