Sage
Overview
Staff Machine Learning Engineer role at Sage. Sage AI is a nimble team within Sage, building innovative services and solutions using generative AI and machine learning to turbocharge our users' productivity. The Sage AI team builds capabilities to help businesses make better decisions through data-powered automation and insights. Responsibilities
Design and implement product features and services that use AI and ML to augment and simplify our customers' workflows Develop our internal ML platform to support our machine learning systems and our own efficiency Monitor and optimize the quality and performance of our models, services, and tools Collaborate with our AI Platform team to extend the capabilities of our machine learning platform Design and write robust production-quality code to support our machine learning systems Build and operate pipelines for accessing and enriching data for machine learning Train, tune, and ship models Mentor other ML engineers, software engineers, and data scientists in best practices Work with product managers and data scientists to translate product/business problems into tractable machine learning solutions You have
Keen interest in artificial intelligence and machine learning and extensive practical experience with it Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. PyCharm, OpenAI, HuggingFace, Spark, Azure, AWS) Extensive experience with cloud environments (AWS, Azure, GCP) Ability to write highly performant code working with big data Bachelor’s degree, preferably in a field that strongly uses data science / machine learning techniques (e.g. computer science/engineering, statistics, applied math) Fluency in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and predictive modelling Strong quantitative and analytical skills with significant experience with data science tools Ability to communicate complex ideas in machine learning to non-technical stakeholders You may have
Experience with one or more ML Ops frameworks — MLFlow, Kubeflow, Azure ML, Sagemaker Strong theoretical foundations in linear algebra, probability theory, or optimization Experience and training in finance and operations domains Deep experience with ML approaches: deep learning, generative AI, large language models, logistic regression, gradient descent Experience wrangling complex and diverse data to solve real-world problems What it s like to work here
You will have an opportunity to work in an environment where ML 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. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Software Development
#J-18808-Ljbffr
Staff Machine Learning Engineer role at Sage. Sage AI is a nimble team within Sage, building innovative services and solutions using generative AI and machine learning to turbocharge our users' productivity. The Sage AI team builds capabilities to help businesses make better decisions through data-powered automation and insights. Responsibilities
Design and implement product features and services that use AI and ML to augment and simplify our customers' workflows Develop our internal ML platform to support our machine learning systems and our own efficiency Monitor and optimize the quality and performance of our models, services, and tools Collaborate with our AI Platform team to extend the capabilities of our machine learning platform Design and write robust production-quality code to support our machine learning systems Build and operate pipelines for accessing and enriching data for machine learning Train, tune, and ship models Mentor other ML engineers, software engineers, and data scientists in best practices Work with product managers and data scientists to translate product/business problems into tractable machine learning solutions You have
Keen interest in artificial intelligence and machine learning and extensive practical experience with it Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. PyCharm, OpenAI, HuggingFace, Spark, Azure, AWS) Extensive experience with cloud environments (AWS, Azure, GCP) Ability to write highly performant code working with big data Bachelor’s degree, preferably in a field that strongly uses data science / machine learning techniques (e.g. computer science/engineering, statistics, applied math) Fluency in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and predictive modelling Strong quantitative and analytical skills with significant experience with data science tools Ability to communicate complex ideas in machine learning to non-technical stakeholders You may have
Experience with one or more ML Ops frameworks — MLFlow, Kubeflow, Azure ML, Sagemaker Strong theoretical foundations in linear algebra, probability theory, or optimization Experience and training in finance and operations domains Deep experience with ML approaches: deep learning, generative AI, large language models, logistic regression, gradient descent Experience wrangling complex and diverse data to solve real-world problems What it s like to work here
You will have an opportunity to work in an environment where ML 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. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Software Development
#J-18808-Ljbffr