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 ONIf 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 WITHYou 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 BRINGTo 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
Skills Required
- 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 machine learning engineering or related fields
- Demonstrable technical leadership, engineer mentoring, and value delivery in an agile product model
- Strong analytical mindset and experience leading problem solving
- Proficiency writing robust, maintainable, and extensible Python code using Docker and CI/CD
- Expertise with agile development and test-driven development
- Expertise in data structures, data modeling, and software architecture
- Expertise producing predictive or mathematical optimization models and deploying them to production
- Expertise in MLOps across experimentation, production, and measurement
- Familiarity with Scikit-learn, PyTorch, TensorFlow, Spark, FastAPI, or similar frameworks
- Experience with complex datasets, ETL pipelines, SQL, and general data engineering
- Expertise with AWS cloud architecture, especially ECR, SageMaker, Lambda, and API Gateway
- Familiarity with Airflow or Databricks Workflows
- Experience with database technology such as Postgres or Redis and data processing technology such as SageMaker or Databricks
- Expertise with Spark, Kubernetes, Docker, Jenkins, Databricks, or Terraform
- Effective communication with team members, stakeholders, business partners, and through code
- Experience influencing technical strategy across technical design and implementation
- Proficiency providing technical leadership and mentorship
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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