Lead Machine Learning Engineer

PRIO conducts research for a more peaceful world, and is committed to using the best of what technology has to offer to achieve that purpose. Having been at the forefront of data-driven social science research since its foundation in 1959, PRIO seeks to strengthen its data science competence by inviting applications for a three-year, full-time position as a Lead Machine Learning Engineer.

The successful candidate will join VIEWS, our conflict forecasting research team, specializing in predictive models using machine learning. The team has a track record of successfully creating and deploying advanced models since 2017 at PRIO and the University of Uppsala. Parts of the codebase for VIEWSis well developed, whereas other parts need development. As our project has expanded, we are looking for an engineer who can design and build a robust and scalable infrastructure for end-to-end model deployment while following MLOps best practices.

As a Lead Machine Learning Engineer, you will play a crucial role in the deployment of our new pipeline (for a current research-focused implementation see link). Collaborating closely with our team of data scientists and researchers, you will contribute to the development and implementation of the infrastructure. Additionally, you will work with, and potentially manage, external consultants during the initial phase of the project. Once the pipeline is successfully deployed, you will be responsible for the maintenance, monitoring, and deployment of new data sources and models developed by our research team.

If you have experience leading cutting-edge ML pipeline deployments or possess a strong interest in taking on such a role, and if you thrive in a challenging, dynamic, and highly meaningful research environment, we encourage you to apply for this exciting opportunity.

Key Qualifications:

  • Strong technical background: Experience in designing and implementing end-to-end ML pipelines using Python, SQL, including knowledge of PostgreSQL, and familiarity with ML frameworks like TensorFlow, PyTorch, and Scikit-Learn.
  • Expertise in building scalable and reliable infrastructure: Demonstrated ability to construct scalable and reliable infrastructure for model deployment using Docker and cloud-based platforms like AWS, while adhering to MLOps best practices. Experience with high-performance computer clustering is a plus.
  • Experience with model versioning and deployment: Proficiency in model versioning and deployment tools such as MLFlow and version control systems like Git. Experience in deploying and managing models in cloud platforms like AWS and internal server environments.
  • Experience with maintenance and monitoring: Track record of effectively monitoring and maintaining ML models in production environments, utilizing tools like Weights and Biases for model tracking, debugging, and collaboration. Familiarity with automated testing and CI/CD processes using GitHub Actions.
  • Strong problem-solving skills: Ability to troubleshoot complex technical issues, propose innovative solutions, and effectively communicate technical concepts to both technical and non-technical stakeholders. Passion for staying up-to-date with the latest ML trends and eagerness to apply new techniques and tools to overcome challenges.

We welcome applicants who possess either relevant experience or a strong interest in taking on a leadership role in ML pipeline deployment within our academic research environment.

PRIO is located in attractive premises in central Oslo. We offer salary according to qualifications, group life insurance, and membership in the Norwegian Public Service Pension Fund. PRIO has an active, social and dynamic work environment with an international staff of approximately 150 members in full and part-time positions. The working language at the institute is English. PRIO is an equal opportunity employer and values staff diversity.

The position is fixed period of three years.

Applications should be written in English, and include the following:

  • Letter of application.
  • Curriculum vitae.
  • Transcripts of academic degrees.
  • Names and contact details of three references.

Applications must be submitted using the online form.

Deadline: 30th June

For further information about the position, please contact Professor Håvard Hegre (hhegre@prio.org). For further information about the recruitment process or the submission of your application, please contact Department Manager Ilze Gehe (ilzgeh@prio.org).


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