Jonas
Hammerseth

Software Developer

Knowit Experience Bergen

Consulting engagement at DNV, working on the Veracity data platform. Building data-driven solutions across backend, ETL, and cloud infrastructure.

Current

Software Developer

AquaCloud

Technical ownership of APIs, ETL pipelines, and analytical systems for salmon biomass and mortality tracking. Built data platform infrastructure with FastAPI, dbt, DuckDB, and AWS. Collaborated with research institutes including Fiskeridirektoratet and FHF.

Board Member & Finance Lead

echo Webkom, UiB

Development and operations of websites for the computer science student organization at UiB. Managed finances and contributed to technical decisions.

Master in Software Development

University of Bergen / Western Norway University of Applied Sciences

Specialized in algorithms, advanced software technologies, programming languages, model-driven software development, and software security.

Bachelor in Cognitive Science

University of Bergen

Specialization in computer science. Focus on machine learning, functional programming, algorithms and data structures.

Budget Tracker

Personal Project · GitHub

Developing a budget tracking tool for personal finance management with expense categorization, periodic payment planning, and graphical consumption visualization. Features an interactive calendar for financial planning and support for shared expenses. Built with Go backend, Svelte frontend, and dockerized PostgreSQL.

Ongoing

Design and Evaluation of a Data Space Service for the Smart Ocean Platform

Master Thesis · SFI Smart Ocean · GitHub

Developed REST API, data forwarding, and database solution for storing and providing access to sensor data. Built with Python, FastAPI, MQTT, and MongoDB.

Shroomy - AI Mushroom Identifier

Academic Project · HVL · GitHub

Developed backend REST API for AI-powered mushroom identification from images. Implemented image classification endpoint using FastAI/PyTorch model with top-5 predictions and confidence scores. Built multi-image prediction feature that averages probabilities across multiple images for improved accuracy. Backend built with Django REST Framework, MongoDB, and OpenCV.