Lead Machine Learning Eng Demand Sensing
Posted on Nov 11, 2018 by Nike
Nike is looking for a Lead Machine Learning Engineer to join our growing team. You will work on a variety of complex business problems such as forecasting, personalization, and inventory optimization. You will work with a team of data scientists to come up with new and interesting hypotheses, test them, and productionalize and scale them in the cloud as APIs, stream processing, or massive batch processing. You will leverage big data, parallel processing technologies, advanced analytics, machine learning, and deep learning techniques to quantitatively plan product demand, allocate resources, and target the right customers with the best products. Above all, your work will accelerate Nike's core mission of serving Athletes*.
What you'll do
- Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets
- Support investigation of new software packages/tools, APIs, and algorithms to deliver quality analytics and machine learning at scale
- Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
- Help drive optimization, testing and tooling to improve data quality
- Iterate on product quality through continuous A/B testing
- Bachelor's Degree in computer science, software engineering, or related field masters or Ph.D. preferred
- Rock solid engineer and data scientist with demonstrated experience in in Machine Learning, AI or distributed systems development.
- Strong background in Machine Learning or a related field. Significant expertise in machine learning algorithms, time series, forecasting, understanding natural language or unstructured data. Deep learning experience is a plus.
- You have experience implementing machine learning systems at scale in Java, Scala, Python or similar (not just R, Octave, or Matlab)
- You have a strong mathematical background in statistics and machine learning
- You care about agile software processes, data-driven development, reliability, and responsible experimentation
- You preferably have experience with data processing and storage frameworks like Hadoop or S3, Snowflake, Spark, Flink, Cassandra or Dynamo, Kafka, etc.
- You'll have experience with at least one these ML frameworks, tensorflow, Caffe, PyTorch.
- You preferably have machine learning publications, project code, or work on open source to share with us