Machine Learning Engineer

As the world leader in SaaS Management and Optimization, Zylo enables companies to organize, optimize, and orchestrate SaaS. Organizations large and small trust Zylo's enterprise-proven technology and unparalleled SaaS Management expertise to optimize more than 30 million SaaS licenses and $23 billion in SaaS spend. Zylo's patent-pending, AI-powered Discovery Engine provides continual, frictionless monitoring of SaaS spend, licenses, and usage to create the industry's most trusted SaaS system of record. Fueled by more data than any other provider, Zylo delivers insights that allow you to take action quickly to optimize growing SaaS portfolios. 

Overview:

We are looking for a Machine Learning Engineer who will help bring Zylo’s discovery engine into the next phase of growth. The ideal candidate is comfortable with large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. This is a unique opportunity to help improve and support our data science infrastructure and work with a devoted group of people that are eager to empower the future of software. 

What you will do:

• Design, develop, and deploy machine learning models and algorithms that remedy business problems and improve operations.
• Develop and maintain scalable, reliable, and efficient systems for data processing, feature engineering, and model training and evaluation.
• Design, develop and enhance the data pipelines.
• Work with engineering, and internal stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and examine data to drive optimization and improvement of product development and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Own the Zylo discovery model and the continued maintenance of it. The Discovery Model is a patent-pending collection of models and is a crucial piece of Zylo’s overall architecture.
• Use predictive modeling to increase and refine the customer experience in the Zylo product.

What you will have done:

• 5+ years of experience in Data Science/Machine Learning
• 2+ years of hands on data science experience in machine learning algorithms with aptitude to show successful outcomes 
• 2+ years of hands on software engineering experience
• Experience as a data engineer, with a strong understanding of data architecture, data modeling and ETL processes 
• Fluency in Python (numpy, pandas, scipy, etc) 

Nice to have:

• Experience in building machine learning infrastructure on AWS, Google Cloud, or Azure.
• Knowledge in Scikit-learn, Tensorflow, and/or PyTorch 
• Experience with big data technologies like Kubernetes, Spark, Bigtable, Hadoop, MapReduce, Postgres, MongoDB, Elastic Search, Cassandra, Spark, NoSQL, and SQL.
• Experience in developing and supporting large scale computational resources on cloud-based Linux infrastructure.

At Zylo, we’re committed to furthering diversity, equity and inclusion and living up to our value of Growing Stronger Together. We’ve worked with our hiring team to craft job descriptions that accurately reflect the nature of the role and minimum qualifications to be successful. If your experience meets the minimum requirements, we strongly encourage you to apply. And if you’re not quite there yet, please consider submitting your resume to our talent community - we’d love the opportunity to get to know you.