Senior ML Engineer - Data & MLOps Lead

Phillips 66 Company; Houston, Northern (TX, KY); Hybrid; USD 125,000 - 153,000; Full time

Benefits offered by this job

VCIP bonus

401k match

Medical/Dental/Vision benefits

Well-being programs

Job summary

Phillips 66 is seeking an Advisor III, Machine Learning Engineering (Data & MLOps) to own the full lifecycle of production-grade AI/ML solutions. The role collaborates with data professionals, software engineers, and business leaders to deploy reliable AI products across diverse domains.

Responsibilities span design, development, validation, deployment, monitoring, and continuous improvement of ML solutions, with emphasis on scalability, governance, and collaboration across enterprise platforms

Qualifications

• 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.

Responsibilities

• Own the end-to-end delivery of ML models and AI-enabled products from design to production, including monitoring and improvement.
• Take accountability for data prep, feature engineering, model development, evaluation, deployment, and lifecycle governance.
• Apply ML, predictive analytics, and stats to identify patterns, generate insights, and automate processes to improve business performance.
• Develop scalable data and ML pipelines for production data storage, transformation, and serving.

Skills

Machine learning

Data engineering

Analytics

Independent problem solving

Education

Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, Physical Sciences, or a related field

Tools

Microsoft Azure

AWS

Databricks

LangChain

LlamaIndex

Semantic Kernel

Power BI

TensorFlow

PyTorch

scikit-learn

Python

C#

Job description

Phillips 66 is seeking an Advisor III, Machine Learning Engineering (Data & MLOps) to own the full lifecycle of production-grade AI/ML solutions. The role collaborates with data professionals, software engineers, and business leaders to deploy reliable AI products across diverse domains.

Responsibilities span design, development, validation, deployment, monitoring, and continuous improvement of ML solutions, with emphasis on scalability, governance, and collaboration across enterprise platforms