Role overview
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.
What you'll work on
- 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.
What we're looking for
- 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.
Tags & focus areas
Used for matching and alerts on DevFound Matlab Time Series Analysis Continuous Integration Python C Natural Language Processing Application Design Cicd Machine Learning Data Science