Engineer ai állások, munkák VIII. kerületben

• Design, build, and maintain backend services and APIs using C#/.NET Core in a cloud (AWS) environment
• Development of scalable and secure microservices supporting SaaS products
• Implementation and support of end-to-end features using Angular
• Participation in code reviews, testing, and debugging

• Automation and streamlining of fraud investigation processes
• Improvement of tooling for fraud investigations
• Creation of seamless experience for agents and customers during fraud investigations
• Development of innovative solutions to tackle fraud

• Design, reliability, and operational excellence ownership of cloud and hybrid infrastructure
• Definition, tracking, and improvement of service reliability using SLO/SLI frameworks
• Driving availability, latency, and scalability targets across platforms

• Design and write clean, scalable Python code
• Build and maintain APIs and data pipelines using FastAPI, SQLAlchemy, and Pandas
• Support and integrate machine-learning workflows into production systems
• Store, process, and optimize 2D, 3D, and GIS data at city scale

• Ownership and evolution of Cypress and TypeScript E2E automation framework
• Integration of automated test suites into CI/CD pipelines
• Research and implementation of load and performance testing strategies
• Application of AI-assisted tools for test generation and failure triage

• Building and maintaining robust and scalable backend systems
• Tackling significant development tasks independently
• Contributing to project delivery
• Collaborating closely with the team on feature implementation and issue resolution
• Playing a key role in cross-team collaboration

• Configuration and evolution of enterprise AI platforms and orchestration components
• Implementation of platform capabilities and contribution to AI use case implementation
• Development of APIs, service components, and integration logic for AI-enabled solutions

• Ownership of quality and test strategy for critical backend services, APIs, and data flows
• Design, implementation, and maintenance of automated test suites in Python covering API, integration, and service-level testing

• Providing technical assistance and guidance to Wise's data engineering and machine learning community
• Taking ownership of difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

• Design Azure cloud infrastructure to support Databricks and data platform workloads
• Implement Azure cloud infrastructure to support Databricks and data platform workloads
• Manage Azure cloud infrastructure to support Databricks and data platform workloads

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM for efficient model deployment
• Implementing and optimizing ML models using quantization, kernel fusion, and efficient batching

• Design, development, and optimization of core ML models in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, code review and sharing best practices

• Software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms
• Creation of software stacks for Arm’s reference platforms for future Arm devices
• Development of test code for software stacks

• Translation of AI opportunities into executable technical solution designs
• Definition of integration approaches with IT and business application/data owners
• Implementation of AI use cases using enterprise AI services and LLM APIs

• Development, simulation, and optimization of manufacturing and production systems
• Manufacturing and process simulation using Tecnomatix Plant Simulation and Process Simulate
• Modeling of material flow, logistics processes, cycle times, resource utilization, and bottlenecks

Embedding with the Ecosystem team to learn the domain, existing tooling, and proven patterns...

• Leading and delivering major projects
• Coordinating release activities
• Analysing test data to support quality improvements
• Supporting software developers in using the platform
• Driving more efficient build and test automated pipelines
• Better controlled use of resources

• Algorithm Design and Implementation for Sensor Data Processing
• Algorithm Creation for Transforming Sensor Data into Actionable Insights
• Development of Techniques for Preprocessing Raw Sensor Data
• Algorithm Optimization for Performance and Scalability
• Integration of Data from Multiple Sensor Types

• Design and develop interactive 3D, XR, and digital twin applications
• Create immersive visualization experiences for industrial, engineering, facility, and enterprise use cases
• Collaborate with 3D artists, designers, software developers, and engineering teams to build high-quality digital environments

• Writing and maintaining clean, high-quality, efficient and well tested code aligning with project specifications
• Architecting and implementing key abstractions bridging Software Engineering and DevOps
• Proactively identifying pain points in the platform and proposing elegant solutions