We're Equinor, an international energy company with a proud history. Formerly Statoil, we are 20,000 committed colleagues developing oil, gas, wind and solar energy in more than 30 countries worldwide. We're the largest operator in Norway, among the world's largest offshore operators, and a growing force in renewables. Driven by our Nordic urge to explore beyond the horizon, and our dedication to safety, equality and sustainability, we're building a global business on our values and the energy needs of the future.
The role of the COO organisation is to drive consistent long term safe and efficient operational performance and value creation. The COO organisation is responsible for the corporate improvement programs and works closely with the line in continuously improving Equinor's performance.
Are you interested and passionate about taking Machine Learning products to production?
The US Data Science team in Equinor is hiring a senior DevOps / Machine Learning Engineer. The team is one of several teams in our Data Science division within our Digital Centre of Excellence. Data science in Equinor is about creating value adding ML technology, not fitting algorithms to a perfect data set.
We believe that data scientists need to be responsible for delivering their models into production. Thus, we are building a container-based machine learning platform to facilitate machine learning deployment. We are looking for someone who is autonomous, passionate about new technologies and willing to help lead in all aspects of machine learning model deployment and operation.
The position is a unique opportunity to build competence around latest data science technologies. In addition, you will enjoy being part of a highly diverse and motivated team with a close link to the OMNIA team.
• Design and implement a container-based Machine Learning platform.
• Implements tools and processes to manage our data science infrastructure and model deployment.
• Craft and maintain documentation of the platform and processes.
• Implement and optimize platform configurations for cost, security, and performance
• Work closely with Data scientists and guide them during the model deployment life cycle, until they are comfortable to deploy Machine learning product themselves
• Coordinate with and contribute to libraries of open source projects such as Kubeflow, Argo, Seldon Core, etc.
• Continuously improve the platform to adopt to new available technologies and to make it more and more automated reducing DevOps burden
• PhD or Master in Computer Science, Statistics, Applied Mathematics, Engineering or equivalent fields
• Expertise in Python
• Expertise in cloud infrastructure (Azure is a plus)
• Experience in managing and deploying container-based services (Docker, Kubernetes, AKS/ACS)
• Experience with microservices and deploying data science products at scale
• Experience with at least one configuration management tools such as Terraform, Puppet, Ansible.
• Experience with working in a DevOps team, incl. knowledge of the GitOPS process and best practices (travis-ci, jenkins…)
In addition, the following is considered a plus:
• Working knowledge of structured and unstructured Data
• Working knowledge of applying Machine Learning algorithms and libraries (Scikit-learn, TensorFlow)
• Working knowledge of Distributed systems and Big Data technologies Hadoop, Spark, Hive
• Ability to live by our safety and security expectations
• You are collaborative and open to new ideas & needs
• You are innovative, self-starting with an inner drive to always improve
• You are willing to take risks and to test and fail fast
• You have good communication skills
• You enjoy working in a diverse and ambitious environment
Equinor offers a competitive salary and a comprehensive benefit package. Equinor is an equal opportunity employer.
Our values are to be courageous, open, collaborative and caring. We believe in these qualities, which are essential for building an even stronger Equinor. If you can identify with them, you could be the one to strengthen our team. Candidates are expected to openly offer all relevant information about themselves during the recruitment process.
All permanent and temporary hires will be screened against relevant sanctions lists to ensure compliance with sanctions law and increase security.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.