Job description
What You’ll Do
Work with model and platform teams to build systems that ingest large amounts of model and feature metadata that will feed into automated monitoring
Partner with product and design teams to build elegant and scalable solutions to speed up governance and monitoring processes
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state of the art, next generation big data and machine learning applications.
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
Use programming languages like Python, Scala, or Java
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployments of machine learning models and application code
Advocate for software and machine learning engineering best practices
Function as a technical lead
As a people leader, you will be responsible for mentoring, coaching, providing feedback, building career plans and assessing performance for your direct reports enabling a high performance engineering team
Basic Qualifications
Bachelor’s Degree
At least 6 years of experience designing and building data intensive solutions using distributed computing
At least 4 years of experience programming with Python, Go, or Java
At least 2 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience with the full ML Development Lifecycle using industry-recognized best practices
At least 2 years of people leader experience
Preferred Qualifications
Master’s Degree or PhD in Computer Science, Electrical Engineering, Mathematics, or a similar field
3+ years of experience building production-ready data pipelines that feed ML models
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2+ years of experience developing performant, resilient, and maintainable code
2+ years of experience with data gathering and preparation for ML models
1+ years of experience leading teams developing ML solutions using industry best
practices, patterns, and automation
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Contributed to open source ML software
Authored/co-authored a paper on a ML technique, model, or proof of concept