Sr. Cloud Infrastructure Engineer – Machine Learning at Sage Intacct
San Francisco, California, United States
🇺🇸 (Posted Jun 26 2019)
About the company
Sage Intacct is 100% invested in meeting the needs of financial professionals, 100% focused on customer success, and 100% committed to the cloud. That’s who we are, and always will be. Thousands of organizations rely on Sage Intacct’s best-in-class cloud ERP software, which is part of the Sage Business Cloud, to deliver the efficiencies and insights that keep them on the fast track of growth, from their first million to their first billion, and beyond.
What distinguishes Sage Intacct most is the company we keep—the employees, partners, and customers that come together to inspire continuous innovation and success. We are the only cloud accounting software company to be appointed a preferred provider by the American Institute of Certified Public Accountants (AICPA) and recognized by finance professionals as the highest rated solution for customer satisfaction. We’ve been ranked a "Top Workplace" for 7 consecutive years and our leadership team includes award winners for Highest Rated CEO, CFO of the Year, and CTO Executive of the Year.
Headquartered in San Jose, we have a nationwide award-winning channel program and a U.S. based customer support team.
Sage Intacct is the innovation and customer satisfaction leader in cloud financial management solutions. Our consistently high employee satisfaction rating is the result of a company culture that truly values our team members’ contributions. Our Artificial Intelligence/Machine Learning team builds capabilities to help businesses make better decisions through data-powered insights.
We are currently hiring a Senior Cloud Infrastructure Engineer to help us build a Machine Learning platform that will provide insights to empower businesses and help them succeed.
As a part of our cross-functional team including data scientists and engineers, you will help steer the direction of the entire company’s Data Science and Machine Learning effort on this greenfield project.
If you share our excitement for machine learning, value a culture of continuous improvement and learning, and are excited about working with cutting edge technologies – please apply!
Production cloud infrastructure for hosting and monitoring machine learning services and APIs.
Infrastructure to allow data scientists and data engineers quick experimentation and training of ML models.
Frictionless scalable deployment pipeline from experiments to production.
What it’s like to work here:
You will have an opportunity to work in an environment where engineering is central to what we do. The products we build are breaking new ground, and we have a focus on providing the best environment to allow you to do what you do best - solve problems, collaborate with your team and push first class software. Our distributed team is spread across multiple continents, we promote an open diverse environment, encourage contributions to open-source software and invest heavily in our staff. Our team is talented, capable and inclusive. We know that great things can only be done with great teams and look forward to continue this direction.
Skills & requirements
Knowledge of, and experience automating cloud infrastructure (AWS or GCP).
Ability to solve problems that span multiple interconnected systems.
Experience with Linux, Kubernetes, Docker, Terraform.
Being able to design and implement end-to-end solutions.
Extremely collaborative and great communication skills.
Understanding of microservices architecture.
You may be a fit for this role if you:
Thrive in a highly technical, engineering focused company.
Take pride in your work while upholding best practices in engineering.
Believe that code should be shipped daily.
Enjoy working in high performing teams, which value learning, shared responsibility and moving fast.
Value pragmatism and simplicity and find pleasure in effectively leveraging technology.