Job Overview
Location
Gothenburg
Job Type
Full-time
Category
Data Science
Date Posted
May 28, 2026
Full Job Description
đź“‹ Description
- • Translate ambiguous business requirements into robust machine learning solutions that solve real-world problems using Python and Google Cloud Platform.
- • Design, develop, and deploy production-grade machine learning models with a focus on scalability, reproducibility, and performance optimization.
- • Conduct end-to-end ML experiments using industry-standard libraries and frameworks, ensuring rigorous testing and validation throughout the model lifecycle.
- • Leverage generative AI techniques to create innovative, client-specific solutions that drive measurable business outcomes.
- • Architect and implement ML systems using Google Cloud services, including Vertex AI, BigQuery, Dataflow, and Cloud Run, ensuring seamless integration with existing data pipelines.
- • Automate ML workflows through MLOps practices, including CI/CD pipelines, feature storage, metadata tracking, and model monitoring.
- • Engineer efficient data flows between databases, data warehouses, and backend systems to support model training and inference.
- • Build and maintain custom Python-based web services or APIs (e.g., using Flask) to expose machine learning models to internal and external clients.
- • Lead client-facing engagements by scoping projects, managing expectations, and presenting technical solutions to non-technical stakeholders.
- • Advocate for high-quality software engineering practices, including version control, code reviews, modular design, and documentation standards.
- • Collaborate with data engineers and analytics teams to ensure data quality, pipeline reliability, and model interpretability across client deployments.
- • Stay current with advancements in machine learning, cloud technologies, and AI ethics to recommend best-in-class approaches for client projects.
- • Mentor junior engineers and contribute to internal knowledge sharing, helping to elevate the technical capabilities of the team.
- • Participate in pre-sales activities by evaluating client use cases, proposing technical architectures, and demonstrating the value of AI-driven solutions.
🎯 Requirements
- • Multiple years of experience as a Machine Learning Engineer, preferably with a consulting background
- • Proficiency in Python for developing production-ready code within CI/CD pipelines
- • Familiarity with cloud platforms such as Google Cloud, AWS, or Azure
- • Hands-on experience with foundational software engineering practices
- • Strong knowledge of SQL for querying and managing data
- • Experience scaling computations using GPUs or distributed computing systems
- • Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python)
- • Strong communication and presentation skills to effectively convey technical concepts
🏖️ Benefits
- • 30 days plus bank holidays
- • 4500 kr per year Healthcare Allowance (paid monthly after probation)
- • Up to 5000 kr per year Wellness Allowance (payable on receipt of invoice)
- • 1200 kr WFH Equipment Allowance (after probation)
- • Access to learning platforms like Udemy
- • Private Salary Sacrifice Pension available
Skills & Technologies
About Datatonic Limited
Datatonic is a London-headquartered data and AI consultancy delivering cloud-native analytics, machine-learning engineering, and business intelligence solutions on Google Cloud Platform and Snowflake. Founded in 2012, the company partners with global enterprises to modernize data stacks, implement real-time analytics, and operationalize AI products. Services range from data strategy and architecture to MLOps, custom model development, and managed support. Certified Google Cloud Premier Partner, Snowflake Select Partner, and Looker Partner, Datatonic serves retail, media, finance, and gaming sectors across Europe and North America.
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