Machine Learning Engineer

Position: Machine Learning Engineer I
WHO YOU’LL WORK WITHWorking 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 FORWe 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, Dev Ops, 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, Tensor Flow).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, Tensor Flow).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 Sage Maker, Docker/containerization, FastAPI.

Experience with inference optimization (latency tuning, caching, embedding serving, and search ranking/information retrievalWHAT YOU’LL WORK ONBuild 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 Tensor Flow) 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.

Summary

Location:

Beaverton, Oregon Type:
Full time