Hykmann Global Business Solutions AB is looking for an experienced Machine Learning Engineer / Data Scientist for an exciting opportunity focused on large-scale geospatial data, machine learning, and data quality improvement.
Term
: 1 Year contract
Are you passionate about building production-ready ML solutions that turn complex datasets into reliable, actionable insights? This role offers the opportunity to work across the entire machine learning lifecycle—from experimentation and model development to integration, deployment, and production-scale delivery.
We’re looking for someone who combines strong data science expertise with solid software engineering skills and a hands-on, ownership-driven mindset.
🎯 About the Role
You will design, develop, and deploy machine learning systems to improve the quality and reliability of large-scale geospatial datasets. Your work will involve classical ML algorithms, NLP, anomaly detection, and large language models (LLMs) to extract structured information and identify data quality issues.
You will collaborate with cross-functional teams to transform analytical models into scalable, production-ready solutions.
🔧 Key Responsibilities
Design, develop, evaluate, and deploy machine learning models.
Build and maintain scalable data pipelines and software solutions.
Apply machine learning and data science techniques to identify anomalies and improve data quality.
Develop classical ML and NLP models to extract structured information from complex datasets.
Work with LLMs, prompting techniques, and agent-based workflows.
Take end-to-end ownership of features and improvements, from experimentation to production deployment.
Integrate ML models into existing systems and production environments.
Collaborate with engineering and data teams to deliver reliable, maintainable, and scalable solutions.
✅ Must-Have Skills & Qualifications
Strong programming skills with extensive hands-on experience in Python.
Proven experience in machine learning and data science, including classification, clustering, feature engineering, anomaly detection, and neural networks.
Practical experience working with LLMs, including prompt engineering and agent-based workflows.
Solid understanding of classical machine learning algorithms, such as SVM, Random Forest, Naive Bayes, and k-NN.
Experience with ML frameworks and libraries, including PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, and Pandas.
Strong analytical thinking, problem-solving, and data interpretation skills.
Ability to balance experimentation and innovation with practical delivery in existing systems.
Excellent written and verbal communication skills.
Proactive approach, strong sense of ownership, and ability to adapt in a fast-paced technical environment.
⭐ Nice-to-Have Skills
Experience with Scala or Java.
Knowledge of Natural Language Processing (NLP), information retrieval, or data mining.
Experience with statistical modelling and predictive model development.
Familiarity with large-scale data processing and production-grade machine learning systems.
👤 Our Ideal Candidate
You are a hands-on ML professional who enjoys solving complex data challenges and building solutions that deliver measurable results. You are comfortable moving between model experimentation, software engineering, and production deployment, and you take responsibility for the quality and success of your deliverables.
You value collaboration, continuous learning, and turning innovative ideas into practical, scalable solutions.
📩 Interested in This Opportunity?
If your experience matches the requirements, send us your updated CV highlighting your Python expertise, machine learning projects, LLM experience, and production deployment capabilities.
Ready to take the next step?
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