Software development engineer állások, munkák VIII. kerületben

• 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

• Ownership and evolution of Tulip’s Cypress + 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 to accelerate test generation and triage failures

Web alapú vállalatirányítási rendszer fejlesztése...

• Technical expertise and influence across LLVM compiler development for Arm and upstream
• Mentoring engineers inside the LLVM team and in the community
• Representation of Arm in the LLVM ecosystem with leadership in upstream contributions and community direction

• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

Szakmailag irányítod és összefogod az analitikus CRM és lakossági adatmenedzsment terület munkáját, biztosítva az analitikus szakértők szakmai támogatását, fejlesztését és feladataik összehangolását....

• Design and build artificial intelligence and machine learning solutions for enterprise clients
• Operationalize AI and machine learning solutions combining custom models with cloud and third-party AI services
• Assess client needs and data for AI/ML solutions

• System IP microarchitecture specification and design
• SystemVerilog RTL verification and debug
• Formal bring-up of non-trivial IP blocks to achieve required quality levels

• Contribution in SystemVerilog RTL verification and debug
• Formal bring-up of non-trivial IP blocks to achieve required quality levels
• Collaboration with engineers across design, performance modelling, validation, and implementation to meet functional requirements, performance, power and area goals

• Design process of a SoC by integrating the latest Arm IP products
• Development of RTL code using System Verilog
• Running EDA tools to check the design and analyze results
• Using AI-assisted engineering tools to support development and debug
• Identifying and fixing bugs

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása

• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

• Development, governance, deployment, and ongoing enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle, including prioritizing initiatives, influencing roadmap decisions, and ensuring successful deployment into production

• Data entry of unstructured property data
• Creation of new databases independently with defined collection criteria and quality standards
• Definition and setup of KPIs for data accuracy and completeness
• Assistance with ad-hoc data and analysis requests

• Risk classification and residual risk handoff
• Severity adjudication and risk framework management
• Vulnerability management including triage and remediation driving
• Design and implementation of compensating controls
• False-positive adjudication with written justification

• Understanding new Arm architecture and IP features and their implementation
• Devising promotion of benefits to software ecosystems and resolving adoption issues
• Analysis and deep understanding of software solutions currently deployed in products

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling including defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Design and configuration of data labeling and processing pipelines
• Combination of multiple data labeling components into automated workflows