Program állások XXIII. kerületben (ai és automatizáció)

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• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• 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

AI-driven vulnerability management. When frontier models can generate thousands of findings in a weekend, the bottleneck shifts from discovery to triage, verification, and remediation. We're building the pipeline that makes this sustainable....

• Building and maintaining infrastructure for large-scale data and video streaming platforms
• Supporting development teams by making deployments easier, faster, and more reliable
• Improving security by helping to monitor and prevent potential risks

• Drive commercial delivery of next-generation tracking products through field trials and full commercial launch
• Shape agentic development culture by organizing development around AI-delegation and AI-augmentation models

• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

• Designing, developing, and improving ball and player tracking algorithms using multi-camera systems
• Owning and evolving multi-view geometry solutions for accurate, court-wide tracking
• Developing robust approaches to occlusion handling, recovery, and failure modes in fast-paced sports scenarios

• Development and improvement of football ball and player tracking algorithms using multi-camera systems
• Contribution to multi-view geometry solutions for accurate tracking across the field of play
• Support for approaches to handling occlusion and recovery in fast-paced sports scenarios

• Technical leadership in Unreal-powered graphics pipeline development
• Mentoring junior engineers
• Collaboration with cross-functional teams
• Development and optimisation of AR/VR and backend graphics solutions
• Integration with in-house art assets
• Addressing critical bugs

• AI-Native Infrastructure: Modern, GPU-intenzív AI/ML keretrendszerek szoftveres alapjainak megtervezése és kiépítése.
• Deep Containerization: Komplex Docker image-ek faragása, kifejezetten GPU-kompatibilis, AI workload-specifikus erőforráskezelésre (NVIDIA-docker, CUDA optimalizáció).

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery of data engineering, ML/MLOps, and cloud migration projects
• Managing and mentoring the data engineering team
• Building and optimizing scalable, high-performance data pipelines

• Design, build, and operate the firm’s AI platform including shared services, APIs, SDKs, and tooling
• Drive architecture across scalability, reliability, security, developer experience, and cost

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and datasets including comprehensive grading rubrics and high-quality golden datasets
• Optimization of judge prompts for automated scoring alignment

• Partnership with Canvas Product and Engineering leaders to set overall strategy for platform experience for Admins and Educators
• Leveraging AI and emerging technologies to create innovative and intuitive product design experiences
• Overseeing a team of designers focusing on the Canvas product space

• Architecting complex AWS infrastructures and zero-day compliant landing zones
• Understanding customers’ business problems and providing technology consulting to identify the best-fit solution
• Owning the end-to-end solution as a key decision-maker and driving the delivery team

• Design and implement core authentication and authorization
• Build and maintain the entitlement decision cache
• Standardize API error handling with correlated request IDs
• Develop catalog APIs with entitled metadata exposure and full-text/faceted search

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Leading a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Providing mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients