Senior Machine Learning Engineer
People make Sage great. From our colleagues delivering ground-breaking solutions to the customers who use them: people have helped us grow for more than thirty years, and people are driving our future as a great SaaS company. We're writing our next chapter. Be part of it!
At Sage, we recognize that the world of work has rapidly shifted over the last few years, particularly how we work. That is why we have committed to working in a hybrid way going forward. Human connection is an essential ingredient of the 4 principles that make up our Flexible Human Work hybrid framework and we want to be transparent in what that looks like when you join our Sage family. On one hand, our offices will continue to play an important role in our future and serve as a place for spontaneous conversations, connection, collaboration as well as focused time. On the other hand, we have learned to reimagine where and when we work and to unlock that flexibility and innovation for our colleagues offering them the opportunity to work flex across their home, Sage offices or customer sites.
We invite you to join us and help us write our next chapter. Follow us on our social media sites to join in conversations about open positions and company news! #lifeatsage #sagecareers. If you would like support with your application (or require any adjustments) please contact us at email@example.com for assistance. All qualified applicants will be thoughtfully considered and never discriminated against based on their race, color, age, religion, sexual orientation, gender identity, national origin, disability or veteran status.
Every business on Earth must, in some way, do bookkeeping, accounting, and financial planning to operate. At the outset, these functions may seem like mundane facts-of-life in the process of running a business; however, the skill with which a company does them can have a profound impact not only on their business, but also the world.Our team, within the CTO function, builds cloud-based AI-powered features and products that fundamentally change the way businesses operate.
Sage Artificial Intelligence Labs "SAIL" is a nimble team within Sage building the future of cloud business management by using artificial intelligence to turbocharge our users' productivity. The SAIL team builds capabilities to help businesses make better decisions through data-powered insights.
We are currently hiring a Senior Machine Learning Engineer to help us design and build machine learning solutions 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.
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, apply today!
• Bachelor's degree, preferably in a field that strongly uses data science / machine learning techniques (e.g. statistics, applied math, computer science, or a science field with direct statistics applications)
• Keen interest in machine learning and 2+ years of practical experience with it
• Strong quantitative and analytical skills and experience with data science tools, including familiarity and experience with the scientific Python toolset: numpy, scipy, sklearn, etc.
• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modelling.
• Ability to write highly performant code taking care of large volumes of data
• Excellent written and verbal communication skills, and ability to evaluate and explain technical details clearly
**You may be a fit for this role if:**
- You're comfortable with investigating open-ended problems and coming up with concrete approaches to solve them.
- You know when to use machine learning and when not to!
- You're a deeply curious person.
- You often think about applications of machine learning in your personal life.
• Design and implement services that use machine learning to augment and simplify our customers' workflows
• Develop our internal toolset to support our machine learning systems and our own efficiency
• Monitor and optimize the quality and performance of our models, services, and tools
• Experimenting, training, tuning, and shipping models
• Working with product managers and data scientists to translate product/business problems into tractable machine learning problems.
What's it 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 continuing this direction.
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