Are you excited about enabling machine learning and AI through high-quality, scalable data pipelines? Do you thrive on transforming raw data into structured, production-ready assets that power global data products? Are you passionate about working with the latest tools and technologies in data engineering as part of a successful, global company at the forefront of digitalization?
We are currently seeking individuals with a strong foundation in data engineering, complemented by experience in machine learning/data science and ideally, domain knowledge in automotive or defense sectors.
To succeed in this role, you should meet the following fundamental qualifications:
A Master’s or PhD in a highly quantitative or technical field such as Computer Science, Data Engineering, Data Science, Machine Learning, Statistics, Applied Mathematics, Vehicle Engineering, or another Engineering/Natural Sciences discipline with a strong data or computational focus.
5+ years of professional experience in one or more of the following areas: data engineering, machine learning, large-scale data processing, advanced analytics, or algorithm development.
Proficiency in Python. Familiarity with SQL is essential.
Hands-on experience in building and maintaining data pipelines, working with distributed data processing frameworks (e.g., Apache Spark, Kafka, or Airflow), and deploying ML models in production environments.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, especially in terms of integration into data workflows.
Spoken and written fluency in English.
- Experience form working in an agile way.
- CI/CD experience.
- Experience using JIRA and git.
- Experience from working with and developing machine learning models.
- Experience of the development of deep-learning models.
- Experience working with Transformers and LLM ML architectures.
- Experience working with Federated Learning.
- Experience with the tools and techniques needed for the deployment of ML models in production environments.
- Up-to-date with the latest algorithmic and architectural developments within the areas of ML and AI.
We attach a great importance to your personality and your willingness to develop yourself together with us. As such, we believe that you meet the following:
- You have an interest, desire as well as habit of adopting new technologies.
- You are a strong communicator who is able to quickly create strong relationships.
- You have a highly analytical mindset and are both meticulous and structured.
- You are an initiative taker who is both flexible and sees solutions instead of problems.
- You make sure that your deliverables are of high quality and respect the set deadlines.
As you will be working as a consultant, you thrive in highly international collaborative environments.
We offer
Welcome to Sigma Technology Experience! We’re a company of 35, backed up by the muscles from Sigma Technology Group. As we're currently expanding, we're seeking individuals who believe in the power of Data to make a difference. We value those who aspire to not only work as consultants but also contribute to shaping our workplace, culture, and strategies for ongoing skill development and staying current in our evolving industry.
As a consultant at Sigma Technology, you get the opportunity to work with world-leading companies together with your colleagues. We deliver everything from expert consultant assignments to entire teams and larger projects. Together with your manager, we make sure that you get an assignment that suits both you and us.
We also believe in building long-term professional relationships, and therefore strive to create an environment where you will enjoy working for a long time!
At Sigma Technology, we are incredibly proud of being one of Sweden’s most recommended employers in 2024!
For more information please contact:
Kasper Kristensson,
[email protected]
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Data Engineer
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Sigma Technology Experience
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Göteborg, Sweden
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Calculation & Simulation, Electricity & Automation, System design, Business Intelligence, System development, Business Analysis, Software development, Digitalisation
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2026-05-18
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2026-06-18
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