AI/Machine Learning Engineer

Position Summary The AI/ML Engineer is responsible for designing, developing, and deploying intelligent solutions that solve meaningful business problems across Murphy USA. Unlike narrowly focused machine learning or generative AI roles, this position works across multiple AI disciplines and applies the most appropriate technology to each challenge. Projects may include traditional machine learning, predictive analytics, recommendation systems, optimization, forecasting, agentic AI, generative AI, retrieval-augmented systems, and workflow automation. The focus is not on implementing technology for its own sake, but on delivering measurable business value through practical, scalable AI solutions. This role will help develop and operationalize in-house AI products. The ideal candidate enjoys solving ambiguous problems, experimenting with new approaches, and taking ownership of outcomes. Team members are expected to continually expand their expertise, collaborate across disciplines, and contribute wherever needed to help deliver successful AI products. This position may be filled at Level I, II, or III based on the candidate's demonstrated capabilities, experience, and ability to contribute within the role. Essential Duties and Responsibilities • Design, develop, train, validate, and improve machine learning and AI models. • Select appropriate AI, machine learning, statistical, optimization, or rules-based approaches based on business objectives and technical requirements. • Develop predictive models, recommendation systems, optimization solutions, and agent-based applications. • Create prompts, retrieval strategies, evaluation methods, and AI application workflows when appropriate. • Develop AI-powered solutions using Python, Databricks, PySpark, SQL, and Azure. • Collaborate with Data & Feature Engineers to define data, feature, and quality requirements. • Build secure, maintainable integrations between AI solutions and approved enterprise systems, tools, and services. • Prepare models and AI applications for production deployment, including testing, documentation, versioning, and handoff requirements. • Design and execute experiments and evaluations to improve solution quality, reliability, safety, and performance. • Monitor production results with AI/ML Operations Engineers and incorporate feedback into future iterations. • Conduct exploratory analysis and prototyping to identify promising solution approaches. • Partner with business stakeholders alongside the Manager of AI Implementation & Strategy to understand challenges and translate requirements into technical solutions. • Communicate technical concepts, recommendations, limitations, and results to technical and non-technical audiences. • Contribute reusable frameworks, libraries, development standards, and technical documentation. • Follow enterprise governance, security, privacy, responsible AI, and data-management requirements. • Continuously explore emerging technologies and cross-train across data engineering and AI operations when doing so improves team delivery. Preferred Qualifications • Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or a related quantitative field preferred, or equivalent practical experience. • Experience with Python, SQL, Databricks, PySpark, Azure, and machine learning development. • Understanding of machine learning, optimization, statistical techniques, software engineering principles, and modern AI architectures. • Familiarity with generative AI, retrieval-augmented generation, agentic systems, or model evaluation is preferred. • Ability to balance engineering rigor, experimentation, and practical business needs. • Experience with source control, testing, documentation, and collaborative software development practices is preferred. • Strong problem-solving and critical-thinking abilities. • Ability to work independently, take initiative, and maintain accountability for outcomes. • Intellectual curiosity and a demonstrated commitment to continuous learning. Show more Show less