Engineer II, Machine Learning
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.
Do you enjoy machine learning and working on projects with a growing company? This position 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 of automation, monitoring, scale, and reliability
- Advocate and educate on the value of data directed outcomes, making focusing on the "how and why’ of problem solving.
- Model behaviors that support the company’s common purpose; ensure guests and team members are supported at the highest level
- Ensure all activities are in compliance with rules, regulations, policies, and procedures
- Bachelor’s degree in Data Science, Computer Science, Engineering, Applied Mathematics or any Quantitative field
- 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 2 years of experience using cloud platforms (e.g., AWS, Azure, GCP) for deploying machine learning models
- Minimum 5 years of experience with some, but not all the technologies mentioned in the Specialized Knowledge section
- Familiarity with enterprise products and platforms (e.g., Infor, SAP, Oracle ERP)
- 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 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 containerization, MLFlow, AWS SageMaker, Triton Inference Server, ONNX RunTime, TorchScript, and TensorFlow RunTime
- Experience with version control systems (e.g., GitHub, GitLab)
- Experience implementing computer vision and NLP solutions preferred
- Experience with C++, CUDA, or the NVIDIA RAPIDS suite preferred
- Machine Learning or Data Analytics AWS Specialty certification preferred
- AWS Cloud Practitioner certification preferred
- Databricks Certified Associate Developer for Apache Spark 3.0 certification preferred
- Databricks Certified Professional Data Scientist certification preferred
- Experience implementing computer vision and NLP solutions
- Experience with C++, CUDA, or the NVIDIA RAPIDS suite
- Machine Learning or Data Analytics AWS Specialty certification
- AWS Cloud Practitioner certification
- Databricks Certified Associate Developer for Apache Spark 3.0 certification
- Databricks Certified Professional Data Scientist certification
- All your information will be kept confidential according to EEO guidelines.
- Travel required less than 10%
- Able to periodically work evenings, weekends and odd hours as needed
Travel required less than 10%
Nationwide Medical Plan/Dental/Vision
401(k) and Flexible Spending Accounts
- Weekly Pay
All your information will be kept confidential according to EEO guidelines.