Conviértete en parte del equipo de NIKE, Inc.
NIKE, Inc. hace más que vestir a los mejores atletas del mundo. Es un lugar para explorar el potencial, borrar límites y ampliar los límites de lo que puede ser. La empresa busca personas que puedan crecer, pensar, soñar y crear. Su cultura prospera al abrazar la diversidad y recompensar la imaginación. La marca busca triunfadores, líderes y visionarios. En NIKE, Inc. se trata de que cada persona aporte habilidades y pasión a un juego desafiante y en constante evolución.
Open to remote work except in South Dakota, Vermont and West Virginia.
The annual base salary for this position ranges from $107,700.00 in our lowest geographic market to $212,600.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.Information about benefits can be found here.
WHO WE ARE LOOKING FOR
We seek passionate engineers to join our team. As a Senior 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.
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.
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.
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:
- Bachelor’s degree in Computer Science, or related field. Will accept any suitable combination of education, experience and training
- 5 to 7 years of professional experience in software engineering
- Candidates local to Beaverton, Oregon, are highly preferred.
- 3+ years of experience in the field of Machine Learning Engineering or related fields
- Expertise in MLOps and an ability to articulate the role of MLOps in machine learning development life cycle from experimentation to production and measurement
- 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
- Familiarity with frameworks such as Scikit-learn, PyTorch, Tensorflow, Spark, FastAPI or similar platforms and frameworks
- 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.
- Expertise with data structures, data modeling and software architecture
- Experience with complex data sets, ETL pipelines, SQL, and general data engineering
- Expertise with Spark, Kubernetes, Docker, Jenkins, Databricks, or Terraform is highly desirable
- Strong analytical mindset and experience leading others in problem solving
- Expertise with agile development and test-driven development
- 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
We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.
NUESTRO PLAN DE CONTRATACIÓN
01 Postúlate
Nuestros equipos están formados por diversos conjuntos de habilidades, bases de conocimientos, contribuciones, ideas y antecedentes. Queremos que encuentres la opción perfecta: revisa las descripciones de los puestos, los departamentos y los equipos para descubrir la función ideal para ti.
02 Habla con un reclutador o haz una evaluación
Si te seleccionan para un puesto corporativo, un reclutador se pondrá en contacto contigo para iniciar tu proceso de entrevistas y será tu contacto principal durante todo el proceso. En el caso de los puestos de Retail, tendrás que realizar una evaluación interactiva que incluye una conversación y cuestionarios. Te tomará entre 10 y 20 minutos completarla. Independientemente del puesto, queremos conocerte a ti, a tu yo en su totalidad, así que comparte quién eres, qué te hace singular y qué deseas hacer.
03 Entrevista
Entra en esta fase con confianza: investiga, entiende lo que buscamos y prepárate para las preguntas que nos harán saber más sobre ti y tus antecedentes.
