If you are passionate about AI and ML, enjoy working in a collaborative environment, and are eager to make an impact on cutting-edge projects, we would love to hear from you.
If you are passionate about AI and ML, enjoy working in a collaborative environment, and are eager to make an impact on cutting-edge projects, we would love to hear from you. Join our team and contribute to revolutionizing the power industry with innovative AI and ML solutions!
WHO WE ARE Heimdall Power is a fast-growing Norwegian-born tech company, established in 2016. We have global ambitions and are already present in 15 European countries as well as the U.S. We aim to optimize power grids worldwide, promoting a swift, secure and affordable green energy transition. Our unique offering combines software and sensors to increase capacity in power grids by 30% on average. By enabling more efficient use of existing infrastructure we reduce carbon footprints while at the same time creating value for society, industry and our shareholders.
What will you be working with
Defining the roadmap and scope for AI and ML utilization within the company.
Managing the entire lifecycle of machine learning models, including their deployment to production environments.
Collaborate with the software team to set up ML and data engineering infrastructure.
Design, develop, and train models for integration into our cutting-edge products.
Contribute to the optimization, testing, and development of internal tools for AI and ML applications.
Who are we looking for
Strong background in machine learning, both in theory and practice.
Excellent ability to articulate the intuition and underlying assumptions of ML concepts.
Hands-on experience implementing and maintaining high-scale, production ML systems using Python, Scala, or similar languages. Experience with TensorFlow is a plus.
Proficiency in data engineering, including the setup of data pipelines and obtaining necessary data for model development and evaluation using tools like Databricks, Spark, or other distributed data processing frameworks.
You have a knack for monitoring model performance, and proficiency in MLOps methodologies and technologies is nice to have.
Ideally, experience working with cloud platforms such as Azure or AWS.
Prioritization of agile software processes, data development, reliability, and focused experimentation.
What we offer
A challenging position in a cross-disciplinary team of dedicated and competent engineers
Positive, flexible and trust-based work environment