Python developer állás, munka

• Defining and communicating architectural vision for the Cloud Management Portal aligned with product strategy and customer outcomes
• Making pragmatic architectural decisions balancing modern practices with delivery speed and customer value

• Design of reliable cloud architectures
• Partnership with customers, SRE teams, and internal stakeholders
• Championing automation
• Building reusable Infrastructure as Code templates and utility tools
• Design of secure cloud networks
• Driving customer success
• Operating platforms at scale

• Development and operation of Keycloak/RHSSO-based IAM capabilities on Kubernetes
• Standardization of deployment, configuration, and troubleshooting practices
• Continuous improvement of reliability, security, and automation around the IAM platform

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• 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

• Support the management of user permissions across multiple tools and systems including AWS IAM
• Help maintain and improve security tooling including endpoint protection solutions and infrastructure monitoring tools
• Assist with monitoring security alerts and investigating unusual events

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and curation of high-quality golden datasets
• Optimization of judge prompts for automated scoring
• Full-stack product development contribution
• Integration of automated evaluations into CI/CD pipelines

• Design and implement automated test cases for backend, frontend, or API-based systems
• Collaborate with distributed teams across multiple time zones
• Participate in requirement analysis to ensure testability and clarity

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

• 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

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Develop and maintain scalable web applications using Angular or React
• Build and optimize RESTful APIs and microservices using Node.js, Python or .NET
• Define and manage cloud infrastructure using Infrastructure as Code, such as Terraform or OpenTofu

• LLM/GenAI architektúrák és agentek tervezése
• Ügyfelek fejlesztési igényeinek felmérése, átlátása és rendszerezése
• Specifikációk és rendszertervek készítése
• Prototípusok és PoC-ok létrehozása
• AI-megoldások jó gyakorlat szerinti kialakításában való részvétel

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend

• Új technológiák bevezetése
• Termékfejlesztési igények implementálása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Kapcsolódó alkalmazás- és interfészfejlesztésekben való együttműködés a társszervezőkkel
• Minőségbiztosítási feladatok támogatása

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams