Solid edge állások Érden (it programozás, fejlesztés)

Collaborate with stakeholders to understand the customer needs and with IT management to shape the strategical directions based on internal requirements and market insights (covering problem analysis, diagnosis collection, research, assessment of business operations,...

• Vectorization of 2D data
• Manual 2D/3D GIS data manipulation
• QA/QC of point cloud classification
• Database handling
• Editing and preparing of 2D vector and 3D point cloud data for further processing

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features

• Mastering in layer rendering tasks
• Discovering render errors and re-submitting halted renders
• Creating logs of errors and forwarding them to production managers and CG supervisors
• Creating logs of the versions of finished render layers continuously

• Building and enhancing cutting-edge CAD features
• Developing world-class, testable, and maintainable code
• Collaborating closely with cross-functional teams to align technical innovations with business goals
• Evolving technical architecture and shaping engineering excellence

• Leading a Core Modelling team building the foundational CAD engine
• Regularly reviewing and challenging engineering design documents
• Building and mentoring a high-performing engineering team
• Contributing to strategic planning and execution as part of the Engineering Leadership Team

• Providing technical expertise to build effective and scalable PLM solutions aligning with company standards and strategic objectives
• Supporting validated and non-validated production PLM systems by resolving access, incident and change requests in a timely way
• Enhancing user experience of PLM systems

• Research, develop, implement, and test artificial intelligence algorithms to improve the quality and robustness of the static world model in automated vehicles
• Focus on road structure including lanes, curbs, and drivable trajectories

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Integration of self-driving software into embedded systems running QNX or Linux
• Building and customizing vendor Board Support Package (BSP) for self-driving stack, vehicle system and test infrastructure
• Building custom embedded Linux with Yocto project
• Porting self-driving software to new platforms

• Build, operate, and improve production data pipelines using Python, Airflow, Kubernetes, and related technologies
• Design scalable data pipelines and data models for growing data volumes and processing needs

• Planning the schedule of parallel projects with production managers and directors
• Tracking and communicating progress in production
• Preparing status meetings
• Collaborating with multiple disciplines and teams to maximize development productivity

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices