Machine Learning Engineer I

Nike; Beaverton (OR); On-site; USD 95,000 - 135,000; Full time

Benefits offered by this job

Interview accommodations

Accessible interview process

Sign language interpreters

Job summary

Nike, Beaverton, OR, is seeking an ambitious Software Engineer I – Machine Learning/AI to join Global Technology. You will collaborate with ML/AI stakeholders and build cloud-native ML solutions that impact Nike's digital channels, with a focus on production-grade systems.

Work with Python, AWS SageMaker, Docker, and modern ML frameworks to design, train, and deploy models, while ensuring responsible AI and scalable data pipelines.

Qualifications

• Bachelor's degree in information technology, computer science or related field, or suitable mix of education/experience.
• 1+ years’ experience building and deploying ML models in production with Python and at least one major ML framework.
• Strong communication skills to translate business goals into technical requirements.
• Experience with data pipelines and distributed systems (e.g., Spark, Airflow) to support ML workflows.
• Experience delivering production-grade LLM/agent workflows, including tool calling, orchestration, and retrieval-augmented generation.
• Ability to collaborate across functions with ownership and a collaborative mindset.
• Experience with CI/CD, testing strategies, and safe rollout patterns.

Responsibilities

• Build and deploy ML models that improve recommendations, ranking, and personalization.
• Own problems end-to-end from data exploration to production deployment.
• Develop scalable ML pipelines using Spark and Airflow.
• Apply modern ML frameworks to design, train, and optimize models in production.
• Contribute to experimentation frameworks including A/B testing and offline evaluation.
• Collaborate with Product and Engineering to translate questions into ML solutions.
• Ensure responsible AI practices, fairness, transparency, and safety in development.
• Take ownership of delivering high-quality solutions from insight to impact.

Skills

Communication skills

Python

ML in production

Agile mindset

Education

Bachelor's degree in IT/CS

Tools

AWS SageMaker

Docker

Spark

Airflow

PyTorch

TensorFlow

FastAPI

Job description

Who You’ll Work With

Working as part of Global Technology’s Machine Learning/AI organization, our team supports the Nike Digital Channels by implementing innovative athlete* facing experiences. You’ll work directly with technical and non-technical Machine Learning/AI stakeholders, athlete*s, and other teams within Global Technology.

Who We Are Looking For

We are looking for an ambitious Software Engineer I – Machine Learning/AI with a passion for cloud-native development and platform ownership. You are someone who thrives in a collaborative environment, is excited by cutting-edge technology, and excels at problem-solving. You have a strong understanding of AWS Cloud Services, Kubernetes, DevOps, Databricks, Python and other cloud-native platforms. You should be an excellent communicator, able to explain technical details to both technical and non-technical stakeholders and operate with urgency and integrity.

To Be Considered For This Position, The Candidate Should

• Have strong technical and non-technical communication skills, including translating business and research goals into technical requirements.
• Bachelor’s degree in information technology, computer science or related field. Will accept any suitable combination of education, experience or training.
• 1+ years’ experience building and deploying machine learning models in production environments with Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow).Strong experience building and deploying machine learning models in production environments
• Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow).
• Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows
• Experience designing and delivering production-grade LLM/agent workflows, including tool/function calling, orchestration patterns, and retrieval-augmented generation (RAG).
• Experience integrating LLM capabilities into existing services and SDLC, including CI/CD, testing strategies (unit/integration + LLM evals), and safe rollout patterns (feature flags, canaries, A/B tests)
• Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset
• Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes
• Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly.
• Experience with AWS SageMaker, Docker/containerization, FastAPI.
• Experience with inference optimization (latency tuning, caching, embedding serving, and search ranking/information retrieval)

What You’ll Work On

• Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement.
• Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment.
• Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery.
• Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimize models in production environments.
• Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset.
• Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions.
• Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor.
• Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

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.