Sr. AI & Machine Learning Engineer

Business Unit Overview Feeding the world is what we do – how we do it is unique. We are not your textbook consumer packaged goods company. While others may be slow to make change happen, Post continuously drives both inorganic and organic growth. Our history is evidence of that fact with over 100 years of heritage and growth from brands that transcend generations like Honey Bunches of Oats, Fruity Pebbles, Malt-O-Meal, Bob Evans, Kibbles 'n Bits, Egg Beaters, Peter Pan peanut butter and more. Our foodservice and ingredient businesses supply other products you love for brands, restaurants and stores. We have more than 55 offices and manufacturing sites and approximately 13,000 employees. Over the past 13 years, Post has made 28+ acquisitions and innovative financial transactions and reached $8.2 billion in net sales in fiscal 2025. During turbulent times of market uncertainty, the food industry has provided a level of stability unlike other industries Post Holdings, Inc. is a Fortune 500® company headquartered in Brentwood, a suburb of St. Louis, Missouri. Our casual professional atmosphere encourages team members to collaborate, innovate and support our operating companies. Our passion and drive advance the reputation of our operating companies and brands—together, we make a difference. Responsibilities Build AI-Powered Business Solutions Develop predictive, optimization, forecasting, recommendation, computer vision, and generative AI applicationsDesign and implement agentic workflows, copilots, and intelligent applicationsTransform high-value business opportunities into scalable production solutionsWork directly with business stakeholders to define requirements and measure outcomes Engineer Production-Ready Systems Design, build, test, and maintain software applications that incorporate machine learning and AI capabilitiesDevelop APIs, services, orchestration layers, and enterprise integrationsBuild user-facing applications that enable employees to interact with AI systemsCreate reusable components and frameworks that accelerate AI delivery across the enterprise Operationalize Machine Learning Develop model training, deployment, evaluation, monitoring, and retraining workflowsEstablish engineering and CI/CD standards for AI application developmentImplement model observability, performance monitoring, and operational controlsEnsure AI systems remain reliable, secure, maintainable, and cost effective Partner Across Enterprise AI Collaborate with Product Managers, Data Scientists, Architects, Security, and Platform teamsContribute to enterprise AI standards, approved development patterns, and governance processesEvaluate and prototype emerging AI technologies, translating promising advances into practical, scalable business solutionsGuide technology adoption by recommending where new AI capabilities fit within the architecture, roadmap, and business prioritiesHelp establish repeatable practices that enable AI delivery at scaleMentor engineers and elevate AI engineering capabilities across the organization Qualifications Required: Bachelor’s degree in Computer Science or a related technical field7+ years of software engineering experienceExperience building production applications used by business usersStrong proficiency in PythonExperience designing APIs, services, integrations, and distributed systemsExperience deploying machine learning models into production environmentsExperience with cloud platforms such as AzureStrong software engineering fundamentals including testing, code quality, version control, and system design Preferred Master’s degree or PhD in Engineering, Computer Science, or a related technical field5+ years of experience with data structures/algorithms3+ years of experience in a technical leadership role leading project teams and setting technical directionExperience building generative AI applications using Azure OpenAI, OpenAI, Anthropic, or similar platformsExperience with AI agents, orchestration frameworks, and Retrieval-Augmented Generation (RAG)Experience with MLOps practices and machine learning lifecycle managementExperience with React, TypeScript, or modern web application frameworksExperience with enterprise data platforms such as Snowflake, Databricks, or FabricExperience working in manufacturing, supply chain, consumer goods, logistics, or enterprise operations This is a hybrid role based in St. Louis, Missouri. In office days are Tuesdays, Wednesdays, and Thursdays.