Data Science / AI Engineer

Curamet; Malmö kommun; On-site; SEK 50,000 - 70,000; Full time

Job summary

Curamet in Malmö, Sweden is seeking a Data Science / AI Engineer to design and develop machine learning models and AI solutions. You will collaborate with cross-functional teams to address business challenges with data-driven strategies.

The ideal candidate will possess strong programming skills, at least 3 years of experience in the field, and expertise in machine learning frameworks. This role offers opportunities to work on innovative AI projects.

Qualifications

• 3+ years of experience in data science, machine learning, or AI engineering.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries.
• Solid understanding of statistical methods and data preprocessing.
• Familiarity with big data technologies and cloud platforms.

Responsibilities

• Design and develop machine learning models and algorithms.
• Collaborate with data engineers to preprocess and transform data.
• Implement and optimize AI models for production environments.
• Monitor model performance and ensure continuous improvement.

Skills

Programming in Python

Machine learning experience

Data preprocessing

Feature engineering

Problem-solving skills

Communication skills

Education

Bachelor's or Master's degree in Computer Science

Tools

TensorFlow

PyTorch

scikit-learn

Keras

Data visualization tools

Hadoop

Spark

AWS

Docker

Job description

Curamet AB

Job Summary

As a Data Science / AI Engineer, you will be crucial in designing, developing, and deploying machine learning models and AI solutions. You will collaborate with cross‑functional teams to understand business challenges, gather requirements, and translate them into effective data‑driven strategies. Your work will build predictive models, develop algorithms, and implement scalable AI solutions to solve real‑world problems.

Key Responsibilities

• Design and develop machine learning models and algorithms to solve complex business problems.
• Collaborate with data engineers to acquire, preprocess, and transform data from various sources.
• Implement and optimize AI models for deployment in production environments.
• Work with cross‑functional teams to identify opportunities for leveraging data to drive business solutions.
• Perform data exploration, feature engineering, and model validation to ensure robust and accurate models.
• Develop and maintain scalable machine learning pipelines and frameworks.
• Monitor model performance and ensure continuous improvement through retraining and optimization.
• Stay up-to-date with the latest advancements in AI, machine learning, and data science to propose innovative solutions.
• Communicate results and insights to both technical and non‑technical stakeholders.
• Document processes, models, and algorithms for reproducibility and knowledge sharing.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 3+ years of experience in data science, machine learning, or AI engineering.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit‑learn, or Keras.
• Solid understanding of statistical methods, data preprocessing, and feature engineering techniques.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Familiarity with big data technologies such as Hadoop, Spark, or NoSQL databases.
• Knowledge of cloud platforms (AWS, Azure, Google Cloud) and containerization (Docker, Kubernetes).
• Strong problem‑solving skills and ability to work independently and in a team.
• Excellent communication and presentation skills.

Preferred Qualifications

• BSC Computer Science, Data Science, or a related field.
• Experience with natural language processing (NLP), computer vision, or deep learning.
• Knowledge of MLOps and experience with CI/CD pipelines for machine learning.
• Familiarity with version control systems such as Git.
• Experience in the industry‑specific domain (e.g., finance, healthcare, retail).