6 data engineering jobs found in Basel

The Machine Learning Engineer will lead the development of the core algorithms powering Moonlight’s AI platform. This high-impact role drives execution of the R&D roadmap, sitting at the intersection of computer vision, engineering, and product development. Responsibilities: Develop, validate, and document deep learning algorithms to extract molecular results from whole slide images Lead experimentation to build novel algorithms: define hypotheses, execute experiments, and iterate while protecting the critical path Collaborate closely with clinical, product, and business functions to translate requirements into model specifications Partner with data engineering to build scalable pipelines for data processing, traceability, and compliance Contribute to building Moonlight’s AI platform, including model integration, performance optimization, and deployment workflows Develop explainability and interpretability methods to support clinical trust and validation...

As a Data Engineer, you will build and implement the core data, ML, and deployment infrastructure that enables scalable, reproducible, and traceable machine learning systems for use in clinical diagnostics. In addition, your code will ensure the traceability and quality of all digitized data from ingestion to research, model development, clinical validation, and inference. This high-impact role spans data engineering, MLOps, and ML platform development in a regulated environment. Responsibilities: Build robust data ingestion pipelines for multi-modal datasets consisting of gigapixel images paired with genomic results and clinical metadata Together with the Software Engineer, design unit testing, logging, and controls to ensure a high-quality and complete data warehouse spanning structured and unstructured data Ensure data quality, consistency, and traceability by authoring the ML platform that enables training, evaluation, deployment, and monitoring of ML models...

Basel 80–100% | immediately or by arrangement Do you want to actively contribute to improving data quality and sustainably strengthen the use of data within your organization? In this role, you will play a key part in the operational management and measurable improvement and further development of data quality. You will create transparency regarding the status of critical data, analyze deviations, and drive targeted improvement measures. You will work closely with data owners, data stewards, business units, and IT. Become part of the team and apply now! Here's how you can get involved: Defining, maintaining, and further developing entity-specific data quality KPIs for prioritized business data objects Setting up and operating targeted monitoring for critical business data objects, including transparent presentation of status, trends, and improvements. Analyzing quality deviations at the data object level and conducting structured root cause analyses in close...

THE OPPORTUNITY Are you an AI-native software engineer ready to shape how enterprise brands appear in AI? The Adobe Brand Visibility team builds the systems that determine how enterprise brands appear in ChatGPT, Gemini, and the next generation of AI agents. We're looking for an AI-native Lead Software Engineer who architects platforms with multi-year relevance, establishes AI-native practices the whole org adopts, and shapes Adobe's technical direction at the intersection of AI and brand intelligence. This role doesn't follow the playbook — it writes it! WHAT YOU'LL DO As an AI-native Software Engineer, you'll operate across team boundaries. You'll define AI architecture strategy for systems that are AI-debuggable across service chains. You'll build shared tooling - MCP servers, skills, pattern libraries — that raises the engineering floor across the org. Build and ship features for Brand Visibility - an AI-first product that helps enterprises optimize their...

THE OPPORTUNITY Are you an AI-native software engineer ready to help enterprises stay visible in the era of AI? The Adobe Brand Visibility team builds the systems that determine how enterprise brands appear in ChatGPT, Gemini, and the next generation of AI agents. We move fast, build with AI-native practices, and measure success in real customer outcomes. As a Software Engineer, you'll own features end-to-end, run the full spec-driven lifecycle, and help set the standard for what AI-directed development looks like in practice. WHAT YOU'LL DO Build and ship features for Brand Visibility — an AI-first product that helps enterprises optimize their digital presence for AI-driven discovery Design and deliver features independently, from spec through validation, across backend services and data pipelines Drive the full spec-driven lifecycle — write validation criteria before implementation, use multi-session patterns for larger work Configure AI harness setups and...

This role sits at the intersection of   process engineering, applied mathematics, and machine learning , with a strong focus on   real-world industrial impact . You will work closely with engineers and plant operators to: Improve operational efficiency Reduce cost and environmental footprint Increase understanding and robustness of our systems Responsibilities Develop   predictive models   for water treatment processes (e.g., ACF, IEX, RO) Data-driven models (regression, tree-based methods, etc.) Physics-informed or hybrid models Translate   operational data into actionable insights Build simple, robust models that can be used by   engineering and operations teams Analyze plant performance to identify   optimization opportunities Work with multidisciplinary teams (process, automation, software) Support deployment of models into engineering tools or operational workflows...