The Advisor III, Machine Learning Engineering (Data & MLOps) owns the full lifecycle of production-grade artificial intelligence and machine learning solutions-from strategy and design through development, deployment, operation, and continuous improvement-to address high-value business problems across Phillips 66. This role combines strong machine learning engineering capabilities with the data engineering foundation required to build reliable, scalable, and maintainable AI products. The position partners closely with business leaders, data professionals, software engineers, and other technology teams to translate complex requirements into practical solutions. The work may support refining, transportation, commercial, marketing, and other data-intensive business areas, with a focus on improving efficiency, reliability, decision-making, and innovation. What You'll Do - Own the end-to-end delivery of machine learning models, algorithms, and AI-enabled digital products, from solution design and development through validation, deployment, production operation, and continuous improvement. - Take accountability for end-to-end ML solution outcomes, including data preparation, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. - Apply machine learning, predictive analytics, and statistical methods to identify patterns, generate insights, automate processes, and improve business performance. - Develop scalable data and ML pipelines for storing, extracting, transferring, loading, transforming, modeling, and serving data for production systems and machine learning applications. - Design and implement large-scale data processing and modeling solutions using modern cloud, analytics, and open-source data science technologies. - Implement AI/ML solutions across Microsoft Azure, AWS, Databricks, and other enterprise platforms as appropriate for the business need. - Apply MLOps practices to operationalize models and AI products, including reproducible development, automated testing, versioning, deployment, monitoring, retraining, and governance. - Lead cross-functional delivery of ML solutions and remain accountable for model development, validation, production deployment, performance monitoring, and lifecycle management. - Own the translation of business objectives and diverse stakeholder requirements into robust, sustainable, measurable, and supportable AI/ML solutions. - Design, build, and maintain reliable data pipelines and data models that support machine learning, advanced analytics, reporting, and business intelligence. - Support batch and real-time data processing while applying sound data management, data quality, governance, and data storage practices. - Optimize data pipelines, SQL queries, analytical code, model-serving workflows, and distributed computing solutions for performance, scalability, reliability, and cost efficiency. - Prepare clear technical explanations, insights, and recommendations for both technical and non-technical audiences. - Own the ongoing performance and improvement of engineering processes, platform capabilities, and operational practices to increase efficiency and reduce failures and operational risk. Required Qualifications - Legally authorized to work in the job posting country. - Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, Physical Sciences, or a related field. - Three or more years of relevant experience in data engineering, analytics, data science, software development, or machine learning, including the ability to work independently on complex problems. Preferred Qualifications - Experience with cloud-based analytics and ML environments, including Microsoft Azure, AWS, Databricks, or comparable platforms. - Experience with advanced ML platform engineering practices such as experiment tracking, CI/CD, observability, or model platform engineering. - Knowledge of large language models and generative AI, including tools or frameworks such as LangChain, LlamaIndex, Semantic Kernel, vector databases, and knowledge graphs. - Experience with analytics and visualization tools such as Power BI or Databricks. - Strong communication and collaboration skills, including the ability to explain technical concepts to diverse audiences and work effectively with non-technical partners. - Experience implementing data quality and governance practices for structured and semi-structured data. - Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or comparable technologies. - Proficiency in at least one modern programming language, such as Python, C#, Java, Scala, or R. - Working knowledge of MLOps practices and the model lifecycle from development through production operation. Compensation Range This position has a base salary range of $125,100 - $152,900. At Phillips 66, we are committed to pay transparency and competitive, equitable compensation. Each role is assigned a salary grade with a defined pay range, benchmarked against industry peers. Where a candidate offer falls within the posted range depends on the candidate's experience, skills, and alignment with the role's requirements. Offers are made to ensure internal equity and market competitiveness. Our compensation programs are designed to reward performance and support career growth. Total Rewards At Phillips 66, providing access to high quality programs and care for you and your family is important to us. Maintaining a culture of well-being - physical, emotional, social, and financial - is essential for a high-performing organization. When we are at our best, we are poised to deliver exceptional results - personally and professionally. Benefits for certain eligible, full-time employees include: - Annual Variable Cash Incentive Program (VCIP) bonus - 8% 401k company match - Cash Balance Account pension - Medical, Dental, and Vision benefits with an annual company contribution to a Health Savings Account for employees on HDHP - Total well-being programs and incentives, including Employee Assistance Plan, well-being reimbursement, and backup family care services Learn more about Phillips 66 Total Rewards. To be considered In order to be considered for this position you must complete the entire application process, which includes answering all prescreening questions and providing your eSignature on or before the requisition closing date of 10/12/2026. Candidates for regular U.S. positions must be a U.S. citizen or national, or an alien admitted as permanent resident, refugee, asylee or temporary resident under 8 U.S.C. 1160(a) or 1255(a)(1). Individuals with temporary visas such as E, F-1, H-1, H-2, L, B, J, or TN or who need sponsorship for work authorization now or in the future, are not eligible for hire.