Python developer állások Dunakesziben (it programozás, fejlesztés)

• Delivery of agentic solutions across multiple client deployments
• Building and configuring full-stack AI-enabled solutions
• Embedding with client service teams and client teams to understand needs
• Translating client needs into technical and functional requirements

• Working across the software stack including firmware, operating systems, device drivers, compilers, runtimes and middleware
• Developing high-performance software for Arm’s advanced architectures, CPUs, system IP, and integrated sub-systems
• Exploring firmware and OS interactions

• 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

• Fejlesztés és megvalósítás komplex generatív AI alkalmazásokban a felfedezéstől a bevezetésig
• Legjobb gyakorlatok keretrendszerének kialakítása felhőarchitektúrák telepítéséhez AI ügynökök támogatására, költség, teljesítmény és biztonság fókuszával LLM munkaterhelésekhez és vektor kereséshez

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifacts
• Conducting regular 1-on-1s for career development and feedback
• Driving task prioritization, sprint planning, and resource allocation

• Nemzetközi csapat tagjaként hosszú távú tesztelési feladatok különböző projektekben
• Új automatizálási keretrendszer fejlesztése low-code tesztautomatizáláshoz
• A keretrendszer karbantartása, gondozása és folyamatos továbbfejlesztése
• Innováció és új technológiák aktív bevonása és alkalmazása

• 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

• Architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines
• Building scalable, production-grade LLM services and agentic workflows alongside traditional ML systems

• Design and implement data models aligned with industry best practices
• Build and optimize scalable data warehousing and lakehouse solutions and ensure data integrity end-to-end
• Create and own robust ELT pipelines connecting multiple internal and external data sources

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, kubernets, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks before they become threats

• 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

• Support Meridian technical due diligence and transition readiness using AI-assisted software engineering methods
• Analyse OpenStack-style services and surrounding components to map APIs, configuration flows, service dependencies, database usage, and operational assumptions

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, dataset documentation

• Use formal verification algorithms to formally prove the correctness of complicated logic problems
• Identify key behaviors for verification to write clear testplans for complex designs
• Implement testplans using innovative formal techniques
• Drive tools to realize their best performance

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

Shaping and evolving the architecture of MDO network automation capabilities including reusable automation patterns, interfaces and technical guidelines...

• 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

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines