Javascript állások IV. kerületben (ai és automatizáció)

• 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

• ServiceNow megoldások tervezése megfelelve üzleti, funkcionális és megfelelőségi követelményeknek
• Szoros együttműködés a Scrum csapattal backlog elemek átdolgozása, követelmények tisztázása és pontos becslések készítése érdekében

• Leading data projects across the EMEA region including initiatives leveraging artificial intelligence and automation
• Leading and delivering innovation and transformation projects from scoping through to measurable business impact

• Development and improvement of computer vision algorithms for cricket tracking systems
• Building and enhancement of ball and player tracking solutions using multi-camera technology
• Contribution to multi-view geometry solutions to improve tracking accuracy

• 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 deployed in products
• Delivering software improvements to relevant open-source projects

• Maintenance of the Tulip Operating System including building, packaging, and support
• Configuration and maintenance of routing, networking, and device configurations
• Maintenance and addition of bootloader, kernel patches, and device trees on Tulip hardware
• Porting the Tulip OS to other hardware targets

Web alapú vállalatirányítási rendszer fejlesztése...

• Identification of highest-leverage AI opportunities in the developer workflow
• Ownership of foundational architecture and standards for agent modeling and internal tool evaluation and deployment
• Building and improving onboarding, documentation, and discovery layers for engineers

• Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures
• Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers

• Design, development and deployment of scalable, resilient and high-performance components for the Wise Assistant
• Ownership of intent detection systems, contact processing pipelines and routing logic for automation solutions

• Machine learning és computer vision megoldások fejlesztése járműfelismerési és közlekedési alkalmazásokhoz
• Modellek és adatfeldolgozási folyamatok tervezése, implementálása, tanítása és kiértékelése

• Designing and developing backend services and APIs that support real-time data ingestion, transformation, and delivery
• Building scalable, low-latency, high-throughput systems capable of handling demanding performance requirements

• Working on the next generation vehicle's self-driving software
• Development of the internal data distribution and execution framework
• Integration of third-party frameworks
• Sensor data recording related tasks
• Development of human-machine interfaces and data visualization tools

• Design and implement APIs and domain services that abstract the complexity of using an LLM and enable rapid feature development from product teams
• Build scalable AWS infrastructure for LLM interactions, including prompt management, context handling, auditing, and response processing

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

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

• Building and maintaining simulation environments for mobile robotic perception and navigation
• Developing and integrating robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• Architect and scale high-performance distributed AI infrastructure on-prem or in the cloud
• Integrate NVIDIA technology into HPC architectures to support scientific and engineering applications
• Champion Deep Learning and Infrastructure among the NVIDIA technical community

• Leading architecture design
• Driving technology decisions
• Co-creating innovative products
• Mentoring clients to adopt Agile practices and engineering excellence
• Leading project workstreams
• Building scalable solutions using Agile methodologies
• Co-creating products with client teams

• Az Agentic AI Platform vállalati integrációs rétegének kialakítása és továbbfejlesztése.
• MCP-szerverek és connectorok fejlesztése és üzemeltetése, amelyek szabványosított és szabályozott hozzáférést biztosítanak az AI-agentek számára a vállalati rendszerekhez és eszközökhöz.