Senior Machine Learning Engineer

Who we are 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 businessesmake better decisions through data-powered insights. We are currently hiring a Senior Machine Learning Engineer to help us build machine learning solutions that will provide insights to empower businesses and help them succeed. As a part of our cross-functionalteam 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 areexcited about working with cutting edge technologies, apply today You will Design and implement product features and services that use machine learning to augment and simplify our customers' workflows Develop our internal toolset to support our machine learningsystems and our own efficiency Monitor and optimize the quality and performance of our models, services, and tools Collaborate with our AI Infrastructure team to extend the capabilities of our machine learning platform Write production-quality code to supportour machine learning systems Build and operate pipelines for accessing and enriching data for machine learning Train, tune, and ship models Work with product managers and data scientists to translate product/business problems into tractable machine learningsolutions You have Keen interest in machine learning and 2+ years of practical experience with it Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. Pandas, NumPy, Spark) and databases (incl. DynamoDB, Postgres)Extensive experience with cloud environments (we use AWS) Ability to write highly performant code working with large volumes of data Bachelor’s degree, preferably in a field that strongly uses data science / machine learning techniques (e.g. statistics, appliedmath, computer science, or a science field with direct statistics applications) Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modelling Strong quantitative and analytical skills with minimum3 years of experience with data science tools, including familiarity and experience with the scientific Python toolset: numpy, scipy, sklearn, etc Ability to communicate complex ideas in machine learning to non-technical stakeholders You may have Experiencewith one or more ML pipeline automation frameworks — MLFlow, Kubeflow, etc Strong theoretical foundations in linear algebra, probability theory, or optimization Deep experience with ML approaches: logistic regression, gradient descent, regularization, cross-validation,overfitting, bias, variance, convex optimization, eigenvectors, relational databases, SQL, latency, computational complexity, sparse matrices Understanding of when to use machine learning and when not to Ability to wrangle data like a pro alligator wrestlerand come out relatively unscathed Curiosity about applications of machine learning in your personal life 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 arebreaking 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 promotean 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.