Salary
💰 SEK 1,050 - SEK 1,100 per hour
Tech Stack
BigQueryCloudGoogle Cloud PlatformKeras.NETNumpyPandasPythonPyTorchScikit-LearnTensorflow
About the role
- Konsultuppdrag som Senior Data Scientist / Data Engineer i Stockholm (hybrid)
- Bygga, driftsätta och operationalisera ML/LLM-lösningar och pipelines på Google Cloud Platform (Vertex AI, BigQuery, Dataflow, Cloud Functions, Cloud Run)
- Utveckla och debugga maskininlärningspipelines i Python
- Sätta upp och hantera utvecklingsmiljöer, inklusive Jupyter Notebooks, för effektiv modellutveckling och experimentering
- Ansvara för kunskapsöverföring: förklara best practices, arkitekturval och skalbara AI-setup på GCP
- Implementera Responsible AI-principer: modellövervakning, datastyrning, fairness och explainability
- Samarbeta med team, stödja delade mål och främja lärande
- Delta i designbeslut kring CI/CD och versionshantering för ML-lösningar
Requirements
- Proven experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Dataflow, Cloud Functions, and Cloud Run
- Strong Python programming skills, including building and debugging machine learning pipelines
- Problem-solving mindset: strong analytical skills and ability to take ownership and drive solutions independently
- Excellent communication abilities and fluency in English
- Skilled in knowledge transfer: able to explain best practices, architecture choices, and scalable AI setups on GCP
- Team-oriented mindset: supports shared goals, takes ownership, and fosters learning
- Proficient in setting up and managing development environments, including Jupyter Notebooks
- Deep practical knowledge of ML frameworks: scikit-learn, TensorFlow, PyTorch, Keras
- Experience with LLMs and Generative AI: Gemini, LangChain, Hugging Face
- Data processing: Pandas, NumPy
- Visualization: Matplotlib, Seaborn
- Responsible AI practices: model monitoring, data governance, fairness and explainability
- Version control & collaboration tools: Git, GitHub/GitLab, CI/CD workflows
- Nice to have: Experience with MLOps principles and tools
- Nice to have: Experience with Microsoft Power Platform
- Nice to have: Exposure to DevOps practices and infrastructure-as-code