Embedded software developer ai állás, munka

• Drive business development efforts focused on Technology Transformation and Data & AI solutions within the local market.
• Build and maintain strong relationships with local financial institutions, including banks and wealth and asset managers.

Develop tools that enable large-scale forecasting and modelling of market sizes, market shares, and other key indicators across Statista's market insights coverage....

implement and productionise ML-based services on our AI- and big-data-platform Databricks, using Python, SQL and Linux....

• System Ownership & Lifecycle:
• Own the entire system life cycle
• for our public cloud-based infrastructure, including requirements gathering, architecting, vetting, building, and operational management.
• Automation & Operational Efficiency: Drive significant improvements in
• operational efficiency

As Lead Engineer (f/m/d)* Backend, you will take over the strategic, technical and disciplinary responsibility for one engineering team on our Agent Platform....

• Work closely with world leading experts in the field of Machine Learning and Video Editing
• Directly work in the core processing, render and ML code of our video and audio applications.
• Enhance your skills to remain at the forefront of the newest development, testing, and deployment techniques

Lead the design, development, and evolution of suena's backend and API infrastructure—ensuring scalability, performance, and reliability as our platform grows....

• Lead technical discovery sessions to deeply understand and map complex merchant requirements.
• Design and present tailored payment solutions, clearly mapping Mollie's APIs and products to specific business needs.

• Implementation of software solutions for research purposes
• Translation of research code into robust software (e. g., optimization, refactoring)
• Contribution to research projects to allow deployment (containerization, virtualization)

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Support the data engineering team in reconciling data between the new and the legacy systems
• Participate in monitoring, troubleshooting, and resolving data processing issues