Engineer II, Machine Learning - Hybrid
Pilot Flying J is the 10th largest privately held company in North America with more than 28,000 team members. As the industry-leading network of travel centers, we have more than 950 retail and fueling locations in 44 states and six Canadian provinces. Our energy and logistics division is a top supplier of fuel, employing one of the largest tanker fleets and providing critical services to oil operations in our nation's busiest basins. Pilot Company supports a growing portfolio of brands with expertise in supply chain and retail operations, logistics and transportation, technology and digital innovation, construction, maintenance, human resources, finance, sales and marketing.
Founded in 1958, we are proud to be family owned and consider our team members to be part of the family. Our founding values, people-first culture and commitment to giving back remains true to us today. Whether we are serving guests, a fellow team member, or a trucking company, we are dedicated fueling people and keeping North America moving.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
Pilot Flying J is part of the Pilot Company family of brands that keeps North America's drivers moving, including E-Z Trip, Mr. Fuel, One9 Fuel Stop, Pride, StaMart and Xpress Fuel.
The purpose of this job is to implement machine learning models into production by utilizing state-of-the-art tools/algorithms and methodologies following DevOps and a test-driven development process.
- Deliver systematic approaches, integrating work into applications and tools with our influence, build and maintain the large-scale analytics infrastructure required for the AI projects, and integrate with external IT infrastructure/service to provide e2e solutions
- Leverage an understanding of software architecture and software patterns to write scalable, maintainable, well-designed, and future-proof code
- Design, develop, and maintain the framework for analytical pipeline
- Design machine learning systems and implement appropriate ML algorithms and tools in collaboration with the data science team
- Implement best MLOps practices for automation, monitoring, scaling, and reliability
- Ensure all activities are in compliance with rules, regulations, policies, and procedures
- Complete other duties as assigned
- Bachelor’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or any Quantitative field
- Master’s degree preferred
- Proficiency in at least one of the following programming languages: Python, C++, or Java
- Minimum 5 years of experience in Data Science, Machine Learning, Software Engineering, or another quantitative discipline required
- Minimum 5 years of experience with some, but not all the technologies mentioned in the Specialized Knowledge section
- Experience architecting machine learning pipelines, including designing, and improving infrastructure for ingesting, storing, and transforming data
- Experience with the usage and implementation of CI/CD pipelines using Jenkins, GitHub Actions, TravisCI, or CircleCI
- Experience with scalable distributed systems hosted on cloud providers
- Experience implementing efficient machine learning pipelines at scale by utilizing distributed and/or GPU hardware optimizations methods
- Experience with data ETL processes and both SQL and noSQL databases and manipulating large structured or unstructured datasets for analysis
- Experience training machine learning models by applying feature engineering, model selection, sampling, and model evaluation strategies using Python frameworks such as scikit-learn, Pandas, Pytorch, NumPy, and PySpark
- Experience developing and deploying scalable implementations of model training and model serving using any of the following technologies: MLFlow, AWS SageMaker, Triton Inference Server, ONNX RunTime, TorchScript, or TensorFlow RunTime
- Experience with version control systems (e.g., GitHub, GitLab)
- Nationwide Medical Plan/Dental/Vision
- 401(k) and Flexible Spending Accounts
- Adoption Assistance
- Tuition Reimbursement
- Weekly Pay
- All your information will be kept confidential according to EEO guidelines.