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Senior Machine Learning Engineer at Accelerate at Iver
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Oslo
Bachelor of Arts (BA), Computational linguistics/Natural language processing
January 1, 2002 – January 1, 2006
University of Oslo
Master of Science (MS), Computational linguistics/Natural Language Processing
N/A – Present
Accelerate at Iver Norge
Senior Machine Learning Engineer
September 1, 2024 – Present
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TIDAL
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August 1, 2018 – July 1, 2021
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Acando Norge
Senior Consultant - Machine learning and search
July 1, 2016 – July 1, 2018
Comperio AS
Senior Consultant
October 1, 2014 – June 1, 2016
Oslo Area, Norway
NTNU
research fellow
November 1, 2010 – January 1, 2015
Universitetet i Oslo
Engineer
March 1, 2010 – November 1, 2014
FAST search technology center, Microsoft
Software Development Engineer
August 1, 2009 – March 1, 2010
Universitetet i Oslo
Engineer
February 1, 2009 – July 1, 2009
Iterate
Solutions Engineer
August 1, 2008 – February 1, 2009
Oslo
Department of Informatics, University of Oslo
Teaching Assistant
August 1, 2007 – June 1, 2008
Oslo
Department of Informatics, University of Oslo
Research Assistant
February 1, 2006 – June 1, 2006
Oslo
Ementor
Senior Consultant
April 1, 2001 – August 1, 2007
Oslo
Ark Skrivervik Data AS
Consultant
January 1, 1999 – April 1, 2001
Oslo
Origo at Norwegian Broadcasting Corporation
January 1, 2016 – Present
Machine learning and search developmen for internal media archive and production tool at Norwegian Broadcasting Corporation (NRK). Engaged in implementing: - Scalable integration and experimental infrastructure for machine learning. - Face/identity tracking system for studio TV show (Dagsnytt atten). - Robust text extraction from radio show audio. - Deep learning based audio classification and segmentation. - Natural language processing (NLP) pipeline for Norwegian Bokmål and Nynorsk. - Content classification across multiple modalities (text, audio, video, images).
Integration of Scandinavian language analysis with search engines
October 1, 2015 – Present
Internal project for integration of Scandinavian language analysis tools and search quality management.
Speaker at Berlin Buzzwords 2015
June 1, 2015 – Present
Held talk at Berlin Buzzwords 2014 on the Search track named "Beyond significant terms" about using Elasticsearch aggregations for real time lexical analysis with applications to entity extraction, keyword trending and guided document filtering.
Text analytics and keyword extraction system for intelligence analysis application
June 1, 2015 – Present
Text analytics and keyword extraction system for intelligence analysis application based on open sources as part of a project for a large customer in the financial sector.
Document profiling for intelligence analysis application
May 1, 2015 – Present
Document profiling for intelligence analysis application based on open sources as part of a project for a large customer in the financial sector.
Semantic Textual Similarity
May 1, 2014 – Present
Developed one of the top performing systems at the STS shared task SemEval 2014.
Native Language Identifaction
April 1, 2013 – Present
Developed one of the top performing systems at the NLI shared task of The 8th Workshop on Innovative Use of NLP for Building Educational Applications (BEA8).
PreseMT Machine Translation project
October 1, 2010 – February 1, 2013
Software developer and researcher in the PreseMT Machine Translation project developing, implementing and integrating natural language models based on very large web corpora.
Lecturer, PhD training course
May 1, 2009 – Present
Grammatical tagging in practice - statistical POS tagging workshop, PhD training course: Infrastructural tools for the study of linguistic variation, 2009.
Cultural Fit Analysis
The candidate has a strong background in academic research and development, transitioning into senior machine learning engineering roles across various companies (media, financial sector, streaming). This diversity indicates adaptability. The focus on NLP and machine learning aligns well with roles requiring deep analytical capabilities. However, the target role 'Data Analyst' might be a slight mismatch given the candidate's extensive experience as a 'Senior Machine Learning Engineer' and 'Research Fellow', which typically involves more advanced model development and less pure data analysis. The projects are diverse in application but consistently revolve around NLP and ML.
Soft Skills & Operational Fit
The candidate's project history, including speaking at conferences and developing top-performing systems in shared tasks, suggests strong problem-solving abilities and a proactive, research-oriented mindset. Experience as a teaching assistant and lecturer indicates good communication and mentoring potential. However, specific details on collaboration styles or project management contributions are not explicitly provided.