ML Engineering Intern

The Infor Decision Analytics and Science (IDEAS) team is responsible for setting the AI/ML strategy at Infor. Our industry-specific Augmented Intelligence (AI) solutions suite in Asset, Forecast, Inventory, Customer, Pricing, Sales, Data and Operational Intelligence domains provides rapid and measurable value to enterprise customers. In pursuit of advancing our AI solutions, IDEAS is currently seeking a Development Intern - Machine Learning (ML). This internship will center on advancing IDEAS’ Time Series (TS) Forecasting Engine, which currently supports probabilistic forecasting using an ensemble of univariate and multi-variate ML models. A Day in The Life Typically Includes: * Explore a new frontier in forecasting by evaluating foundational time series models such as TimesFM, Chronos, Moirai, Unit2TS, etc. that learn broad temporal patterns from massive datasets and can perform zero-shot and few-shot forecasting on entirely unseen series. * Assess how these emerging models perform relative to our existing TS Forecasting Engine using benchmark datasets. * Prototype integration into our current architecture and determine how they could enhance Infor’s AI-driven forecasting capabilities across multiple business domains. * Evaluate whether we can incorporate effective fine-tuning of these new foundational time series forecasting libraries into our production pipeline. * Maintain development artifacts and technical documentation in GitLab. Basic Qualifications: * Final year candidates in the Master's / Engineering program in Statistics, Mathematics, Physics, Computer Science, Operations Research, or a related quantitative discipline from an accredited university. * Software development experience in Python and familiarity with scientific libraries commonly used in statistical analysis and machine learning e.g., pytorch, transformers library, and scikit-learn. Familiarity and basic understanding of PySpark, SQL or other data processing frameworks. * Familiarity with software development environments such as Visual Studio Code, and version control using Git and CI/CD pipelines. * Knowledge of data models, graphs, and relational databases. Proficiency in handling large datasets and data analysis with Tableau, Power BI, or similar BI tools. Preferred Qualifications: * Experience or strong interest in modern ML architectures, including transformers, diffusion models, or foundation models. * Familiarity with task management with JIRA.About InforInfor is where ambition meets impact. Join a global community of bold thinkers and innovators, where your expertise doesn’t just solve problems. it shapes industries, unlocks opportunities, and creates real-world impact for billions of people. At Infor, you’re not just building a career. you’re helping to build what’s next.Infor is a global leader in business cloud software products for companies in industry specific markets. Infor builds complete industry suites in the cloud and efficiently deploys technology that puts the user experience first, leverages data science, and integrates easily into existing systems. Over 60,000 organizations worldwide rely on Infor to help overcome market disruptions and achieve business-wide digital transformation.For more information visit [1] www.infor.comReferencesVisible links1. https://www.infor.com/Our ValuesAt Infor, we strive for an environment that is founded on a business philosophy called [1] Principle Based Management™ (PBM™) and eight Guiding Principles: integrity, stewardship & compliance, transformation, principled entrepreneurship, knowledge, humility, respect, self-actualization.We have a relentless commitment to a culture based on PBM™. Informed by the principles that allow a free and open society to flourish, PBM™ prepares individuals to innovate, improve, and transform while fostering a healthy, growing organization that creates long-term value for its clients and supporters and fulfillment for its employees.Infor is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive work environment. 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