Advisor III, Machine Learning Engineer
Phillips 661 day ago
Houston, TX, USASenior
Base Salary
$125k - $153k/yr
Responsibilities
- Own end-to-end delivery of machine learning models, algorithms, and AI-enabled digital products from design and development through validation, deployment, operation, monitoring, and improvement.
- Build scalable data and ML pipelines for data extraction, transformation, modeling, serving, and production machine learning applications.
- Develop large-scale data processing and modeling solutions across Microsoft Azure, AWS, Databricks, and other enterprise platforms.
- Apply MLOps practices including reproducible development, automated testing, versioning, deployment, monitoring, retraining, and governance.
- Design and maintain reliable data pipelines and data models for machine learning, analytics, reporting, and business intelligence.
- Support batch and real-time data processing while applying data quality, governance, management, and storage practices.
- Optimize SQL queries, analytical code, data pipelines, model-serving workflows, and distributed computing solutions for performance, scalability, reliability, and cost efficiency.
- Lead cross-functional ML delivery and explain technical insights and recommendations to technical and non-technical audiences.
Requirements
- Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, Physical Sciences, or a related field.
- At least three years of relevant experience in data engineering, analytics, data science, software development, or machine learning.
- Experience with cloud-based analytics and ML environments such as Microsoft Azure, AWS, Databricks, or comparable platforms.
- Experience with 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.
- 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.
- Strong communication and collaboration skills and the ability to work independently on complex problems.
Benefits
- Base-eligible employees may receive an annual variable cash incentive program bonus, 401(k) company match, cash balance account pension, and medical, dental, and vision benefits.
- Eligible employees may receive an annual company contribution to a Health Savings Account for HDHP coverage.
- Well-being programs and incentives include an Employee Assistance Plan, well-being reimbursement, and backup family care services.
- Regular U.S. applications must be completed, including prescreening questions and eSignature, by the requisition closing date of 10/12/2026.
Categories
Data EngineeringML Engineering
About Phillips 66
Phillips 66 is a public downstream energy company that refines crude oil into transportation fuels, markets fuel brands (Phillips 66, 76, Conoco), and operates midstream logistics and a petrochemicals joint venture (Chevron Phillips Chemical). It serves consumers, commercial fleets, and industrial customers across the U.S. and internationally. Formed in 2012 via a spin-off from ConocoPhillips, the company is headquartered in Houston and trades on the NYSE (PSX).