> Markdown version of [/jobs/ext/3802335-sr-ai-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3802335-sr-ai-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. AI & Machine Learning Engineer - **Company:** Post Holdings - **Location:** St. Louis, MO, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, Computer Vision, Microsoft Azure, Software Quality, Continuous Integration, Data Structures, Distributed Systems, Python (Programming Language), Machine Learning, OpenAI, Software Engineering, Systems Integration, TypeScript, Web Application Frameworks, Enterprise Data Management, ReactJS, Snowflake, Generative AI, Agentic-AI, Kubernetes, Information Technology, Performance Monitor, Machine Learning Operations, Software Version Control, Databricks - **Published:** October 17, 2026 - **Apply:** https://dejobs.org/x/x/F4D1E0D8D55344DFA6B223F542CCD4D9/job/ ## About the Role * Bachelor's degree in Computer Science or a related technical field * 7+ years of software engineering experience * Experience building production applications used by business users * Strong proficiency in Python * Experience designing APIs, services, integrations, and distributed systems * Experience deploying machine learning models into production environments * Experience with cloud platforms such as Azure * Strong 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 field * 5+ years of experience with data structures/algorithms * 3+ years of experience in a technical leadership role leading project teams and setting technical direction * Experience building generative AI applications using Azure OpenAI, OpenAI, Anthropic, or similar platforms * Experience with AI agents, orchestration frameworks, and Retrieval-Augmented Generation (RAG) * Experience with MLOps practices and machine learning lifecycle management * Experience with React, TypeScript, or modern web application frameworks * Experience with enterprise data platforms such as Snowflake, Databricks, or Fabric * Experience 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. ## Description Build AI-Powered Business Solutions * Develop predictive, optimization, forecasting, recommendation, computer vision, and generative AI applications * Design and implement agentic workflows, copilots, and intelligent applications * Transform high-value business opportunities into scalable production solutions * Work 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 capabilities * Develop APIs, services, orchestration layers, and enterprise integrations * Build user-facing applications that enable employees to interact with AI systems * Create reusable components and frameworks that accelerate AI delivery across the enterprise Operationalize Machine Learning * Develop model training, deployment, evaluation, monitoring, and retraining workflows * Establish engineering and CI/CD standards for AI application development * Implement model observability, performance monitoring, and operational controls * Ensure AI systems remain reliable, secure, maintainable, and cost effective Partner Across Enterprise AI * Collaborate with Product Managers, Data Scientists, Architects, Security, and Platform teams * Contribute to enterprise AI standards, approved development patterns, and governance processes * Evaluate and prototype emerging AI technologies, translating promising advances into practical, scalable business solutions * Guide technology adoption by recommending where new AI capabilities fit within the architecture, roadmap, and business priorities * Help establish repeatable practices that enable AI delivery at scale * Mentor engineers and elevate AI engineering capabilities across the organization