Machine Learning Engineer

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At Exxon Mobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.

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Exxon Mobil's state-of-the-art campus north of Houston serves as home to its Upstream, Product Solutions and Low Carbon Solutions businesses and their associated service groups. The facility opened in 2014 and accommodates more than 10,000 employees and visitors.

By bringing many global functional groups together, the campus provides employees with the tools and capabilities needed today, and in the future, to achieve business objectives and accelerate the discovery of new resources, technologies and products. It was designed to foster improved collaboration, creativity and innovation and enhance the company’s ability to attract, develop and retain the top talent in the industry.

The campus is located in Spring, Texas, on 385 wooded acres immediately to the west of Interstate Highway 45 (I-45), at the intersection of I-45 and the Hardy Toll Road, approximately 25 miles from the cultural vibrancy of downtown Houston.

The campus was constructed to the highest standards of energy efficiency and environmental stewardship. Its design incorporates extensive research into best practices in building and workplace design through extensive benchmarking of the world’s top academic, research, and corporate facilities.

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ML Engineering is a technical field that deals with the automation of deployment and sustainment of Data Science work products at scale to deliver value to customers on a reproducible way.
The Machine Learning Engineer role leads and coordinates work efforts to apply technical skills, domain knowledge and agile techniques to deliver commercial-grade, automated data science solutions including essential data pipeline, ML model retraining pipeline and user interface development in partnership with Data Scientist and business units. Machine Learning Engineer also identifies effective design for new Data Science model deployment and sustainment opportunities and mentors less experienced team members.

• Applies Software Development methodologies, Dev Ops toolsets and ML techniques and coordinates the implementation effort of an end-to-end machine learning workflow that effectively brings ML models to production.
• Contribution:
  Leads the scoping and identifies the appropriate solution design of a deployment of a new data science solution. This may require provisioning deployment environments via Infrastructure as Code, applying
• Continuous Integration & Continuous Deployment principles, developing relevant source code, ML Pipelines, APIs, and user interfaces, and employing multiple testing methods to transform and scale a prototype data science model to a multi-user environment across business lines.
• Sustains solutions by enabling continuous ML model and/or service performance monitoring, training, and re-training of models, including the implementation of proactive alerting methods.
• Sphere of Influence:
  Across projects and business lines, acts as a primary contact for business requests.
• Represents Exxon Mobil in interactions with key competitors, vendors, partners, joint ventures, NOCs, government officials, industry associations, academia, and industry forums.
• Knowledge Sharing:
  Mentors early career professionals and utilizes depth and/or breadth of experience to identify cross-functional…