About this role
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 contractAre 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 RoleYou 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 ResponsibilitiesDesign, 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 & QualificationsStrong 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 SkillsExperience 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 CandidateYou 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?