Machine Learning Engineer - Exxon Mobile : Job Details

At ExxonMobil, 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.

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society's evolving needs.

We are looking to hire candidates to work on challenging technology and engineering problems that span oil and gas exploration & production, chemicals/fuels/lubricants products and low carbon solutions. A successful candidate would understand a business problem (both commercially and technically), translate it into a computational, data science or machine learning problem and apply engineering, numerical, data science and programming skills to tackle it. The Machine Learning Engineer will work as part of a team to design, develop, deploy and sustain data science solutions that are scalable, reproducible and with commercial-grade quality.

• Applies software development practices, DevOps skills and Machine Learning (ML) techniques to orchestrate an end-to-end machine learning workflow that effectively brings ML models to production.
• Participates in scoping of deployment of new data science solutions and implements the appropriate solution design.
• Sustain data science solutions by enabling continuous ML model and/or service performance monitoring, training, and re-training of models, including the implementation of proactive alerting methods.
• Works effectively with computational scientists, data scientists, engineers, software developers, and domain experts across the globe to develop and apply computational and data science solutions in support of our business.

Skills and Qualifications

• Bachelor's degree from a recognized university in Computer Science, IT, Applied Mathematics, Engineering or related disciplines with minimum 7.0 CGPA or equivalent.
• Minimum 3 years of experience in Data Science and Machine Learning or related computational domain.
• Competent to expert level programming experience in C/C++/Python.
• Experience with refactoring legacy code and leveraging third-party libraries/APIs during software development.
• Experience with Source code version control (Git), Azure Cloud platform and containers, Databricks and MLflow.
• Continuous Integration and Continuous Deployment.
• Familiarity with statistical analysis, regression and classification.

• Experience with time series analysis, computer vision, natural language processing.
• Knowledge or hands on experience on Matlab & SQL.
• Strong written and verbal communication skills.
• Prior knowledge of commercial software development and/or experience in commercial software teams.
• Familiarity with Oil and Gas Industry.

An ExxonMobil career is one designed to last. Our commitment to you runs deep our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you:

• Competitive compensation
• Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits
• Global networking & cross-functional opportunities
• Annual vacations & holidays
• Day care assistance program
• Training and development program
• Tuition assistance program
• Workplace flexibility policy
• Relocation program
• Transportation facility

Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company's eligibility guidelines.

ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status.