Machine Learning Engineer
Utel provides Network Monitoring & Analytics solutions to empower quality in telecom networks. Our customers are Communication Service Providers (CSPs), Network Equipment Manufacturers (NEMs), intelligence and police security services, and the military.
We deliver network insights in real-time, helping our customers to capture raw data, analyse it – and present it in a professional, easy-to-understand and intuitive way. With the data, analytics, and insights we provide, our customers can:
- Understand network performance across different domains.
- Run more efficient operations.
- Identify and resolve faults.
- Provide assurance and meet SLA/KPIs.
- Plan investment more effectively.
- Protect against threats, such as fraud.
- Reduce risk exposure and loss.
Founded in 1998, Utel is a subsidiary of Alytic, which is fully owned by Arendals Fossekompani, a green-tech industrial investment company with substantial financial capacity and decades of successful value creation.
We are a team of enthusiastic individuals, blending experience and fresh talent to create a thriving culture and working environment. We deliver solutions to operators around the world, who depend on our expertise and the outstanding support we offer.
We are growing and we want you to bring your creativity, skills, and innovations to help us. Utel’s office is in Grimstad, just down the hill from the University campus.
Utel is currently developing a series of new machine learning tools ranging from automated setup for new customers to fraud detection models and we need your help in exploring the data sets our new models are generating. Can you help us discover new types of telecom fraud in unknown anomalies? Can you help enable our systems to fully map and understand our customers’ networks without any setup required? Can you help create the next ML model for detecting network anomalies? Can you help create internal tooling for exploring, visualising and evaluating our model results? We have a variety of potential tasks we can tailor to your knowledge, skill level, and preferences in machine learning, analytics, and data engineering. Currently our ML focus is centered around anomaly detection and unsupervised learning, but we are continuously expanding the possibilities as our models and data sets grow.
The specific tasks can differ between choice of project, but in general you will:
- Analyze raw and/or aggregated data to look for trends, anomalies, and other interesting findings, both manually and automated.
- Learn about our models and approach to data mining and algorithms.
- Join in on the development process of new models.
- Research and discuss optimal algorithms and strategies for our use cases and products.
We expect you to:
- Be physically present in the office, especially during core working hours 09:00 – 14:00.
- Be curious and ask a lot of questions.
We hope an internship might lead to a master thesis and/or job prospects!
- You are curious and eager to learn about new technologies and how to extract value from real world data.
- Have some experience in unsupervised learning and/or data analysis/exploration.
- Some experience with Pandas or similar data frame tools and/or data visualization tools such as Plotly or Matplotlib is a plus.
- Have some experience in using git.
- Fluent and comfortable with communicating in both English and Norwegian
- Possibility to use applied ML on challenging real world data sets.
- Possibility to help create ML products that help keep critical infrastructure fraud free, trustworthy and ensure its stability.
- Inclusive and helpful colleagues.
- Office location near the University. Good place to study!
- Coffee and snacks.
Please include in your application which tasks that intrigue you in the and which areas of Machine Learning you have experience with or are eager to learn more about. A link to a GitHub account, code examples or reports from recent university tasks/projects are most welcome too, so we can match the tasks to your skill level better.