Productionizing machine learning applications and systems at scale
Participate in the technical design, development, and implementation of machine learning applications
Design, build, and/or deliver ML models and components
Inform ML infrastructure decisions using understanding of ML modeling techniques
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate with cross-functional Agile team to enhance software for big data and ML applications
Retrain, maintain, and monitor models in production
Leverage cloud-based architectures to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Ensure code management to reduce vulnerabilities and governance of ML practices

Requirements

Bachelor’s Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (Preferred)
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (Preferred)
4+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (Preferred)
3+ years of experience developing performant, resilient, and maintainable code (Preferred)
3+ years of experience with data gathering and preparation for ML models (Preferred)
3+ years of people management experience (Preferred)
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents (Preferred)
3+ years of experience building production-ready data pipelines that feed ML models (Preferred)
Ability to communicate complex technical concepts clearly to a variety of audiences (Preferred)

Benefits

Performance-based incentive compensation, including cash bonus(es) and/or long-term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

machine learningPythonScalaJavaML frameworksscikit-learnPyTorchDaskSparkTensorFlow

problem solvingteam leadershipcommunication

Bachelor's DegreeMaster's DegreeDoctoral Degree