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Nike

Senior Machine Learning Engineer, ITC

Posted 26 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in Karnataka, IND
Senior level
Remote
Hiring Remotely in Karnataka, IND
Senior level
Design and implement scalable machine learning, generative AI, prediction, and optimization solutions for Nike’s corporate functions. Build and improve MLOps platforms, data pipelines, and production applications while partnering with stakeholders and technology teams. Provide technical leadership, mentor engineers, influence technical strategy, and deliver robust solutions using cloud, data engineering, and modern ML technologies.
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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 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.

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

  • 5+ years of professional experience in software engineering

  • 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

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.

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