Principal Machine Learning Engineer
About the job
Twilio is looking for a Principal Machine Learning Engineer who wants to design, build, and deploy machine learning systems into the real world and help Twilio power its growth initiatives.
You are eager to learn and inspire, and you like to think at scale and work on real world products and problems. You bring a focus on efficient experimentation, team collaboration, large-scale systems design, and good data science principles.
You deal with ambiguity effectively and are able to bring clarity in requirements and technical solutions. You are a technical lead for the team and partner effectively with product managers and other cross function groups
Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply.
- A Masters or PhD in Computer Science, Mathematics or Statistics.
- Strong background in the foundations of machine learning – depth in Regression, Classification, KNN, RFM, DNN, SVM and Naive Bayes.
- 7+ years of hands-on experience with one of Python, C/C++, Go or Java/Scala
- Strong fundamentals in Systems Design and Computer Science
- Exposure to Big Data technologies(spark/hadoop) and Microservices Architecture
- Exposure to different ML frameworks and services like Sagemaker, Clarify, Model Monitoring, TensorFlow, MxNet, PyTorch, scikit-learn etc.
- Track record of building, shipping and maintaining machine learning models in a highly ambiguous and fast paced environment.
- Track record of defining new data science techniques and best practices that improve the ML model performance
- Track record of designing and architecting large scale experiments and analysis which impact multiple teams and adjacent focus areas