Lead Machine Learning Engineer

About the role

The Lead Machine Learning Engineer (AI/ML) joins the Corporate Functions Artificial Intelligence team at Nike in Karnataka, India, delivering AI capabilities for Nike's corporate functions. Day-to-day, you own projects end-to-end from conception to operationalization, set technical direction, mentor teammates, and design scalable applications leveraging prediction models, optimization programs, and generative AI. You collaborate with globally distributed teammates, business stakeholders, and product owners to solve machine learning problems at scale.

What you’ll do

• Own projects end-to-end from conception to operationalization, demonstrating command of the full software development lifecycle
• Set the technical direction for the team, provide vision and guidance to teammates, and raise the bar on engineering quality
• Design and implement scalable applications that leverage prediction models and optimization programs to deliver data-driven decisions with business impact
• Contribute to core advanced analytics, machine learning, and generative AI platforms and tools to enable prediction and optimization model development
• Work closely with business stakeholders, product owners, and peers within the engineering team to ensure successful delivery of solutions
• Coordinate dependencies with other technology teams that lead the up and down-stream solutions
• Mentor and contribute knowledge and software back to the analytics and engineering communities both within Nike and at-large
• Influence technical strategy through all aspects of technical design and implementation

What you’ll bring

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

Nice to have

• Expertise with Spark, Kubernetes, Docker, Jenkins, Databricks, or Terraform is highly desirable
• 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
• 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 cloud architecture and technologies, especially Amazon Web Services: ECR, SageMaker, Lambda, API Gateway
• Strong analytical mindset and experience leading others in problem solving
• Effective communication skills with team members, stakeholders, the business, and in code

Skills

Education

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