Staff Machine Learning Engineer

OverviewStaff 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.ResponsibilitiesDesign and implement product features and services that use AI and ML to augment and simplify our customers' workflowsDevelop our internal ML platform to support our machine learning systems and our own efficiencyMonitor and optimize the quality and performance of our models, services, and toolsCollaborate with our AI Platform team to extend the capabilities of our machine learning platformDesign and write robust production-quality code to support our machine learning systemsBuild and operate pipelines for accessing and enriching data for machine learningTrain, tune, and ship modelsMentor other ML engineers, software engineers, and data scientists in best practicesWork with product managers and data scientists to translate product/business problems into tractable machine learning solutionsYou haveKeen interest in artificial intelligence and machine learning and extensive practical experience with itExpert 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 dataBachelor’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 modellingStrong quantitative and analytical skills with significant experience with data science toolsAbility to communicate complex ideas in machine learning to non-technical stakeholdersYou may haveExperience with one or more ML Ops frameworks — MLFlow, Kubeflow, Azure ML, SagemakerStrong theoretical foundations in linear algebra, probability theory, or optimizationExperience and training in finance and operations domainsDeep experience with ML approaches: deep learning, generative AI, large language models, logistic regression, gradient descentExperience wrangling complex and diverse data to solve real-world problemsWhat it s like to work hereYou 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 levelMid-Senior levelEmployment typeFull-timeJob functionEngineering and Information TechnologyIndustriesSoftware Development #J-18808-Ljbffr

Created: 2025-09-17