Solution Engineer - Tooling (Vehicle Intelligence)

3 months ago

Munich, GermanyMid Level

H1B Sponsor

Responsibilities

Serve as the primary technical point of contact for customers evaluating Applied Intuition’s simulation and data-management tooling.
Lead demonstrations, proof-of-concept deployments, and integration workshops for the full toolchain.
Support integration of Applied’s platform into customer ADAS/AD CI/CD pipelines across SIL, HIL, and VIL stages.
Guide customers in designing closed-loop data flywheels covering data collection, curation, labeling, scenario extraction, simulation replay, and evaluation.
Help customers configure scenario-based testing and automated pass/fail metrics for validation programs.
Translate customer feedback into actionable product insights for Applied’s engineering team.
Manage technical workstreams and milestones across multi-stakeholder customer programs.

At least 3 years of experience in ADAS/AD development, validation, or simulation at an OEM, Tier 1 supplier, or technology company.
Hands-on experience with automotive software testing methodologies including unit, SIL, HIL, and VIL testing.
Familiarity with CI/CD pipelines in automotive or embedded-software contexts.
Understanding of camera, lidar, radar, and ultrasonic sensor types and their data characteristics.
Experience with data management pipelines involving ingestion, curation, labeling, or scenario extraction.
Bachelor’s degree in computer science, electrical engineering, robotics, or a related field.
Intermediate programming experience in Python and/or C++.
Strong written and verbal English communication skills; German or another European language is a significant plus.
Customer-facing experience and strong communication and presentation skills are preferred.
Experience with a simulation platform such as Applied Intuition, CARLA, IPG CarMaker, dSPACE SIMPHERA, or VIRES VTD is preferred.
Familiarity with dSPACE, Vector, or NI toolchains for HIL/SIL test automation is preferred.
Knowledge of ISO 8800, ISO 26262, ISO 21448, or ASPICE is preferred.
Experience with ML/AI pipelines for model training or perception-system evaluation is preferred.
Background in fleet data operations, OTA, or post-SOP data-driven improvement loops is preferred.

Primarily in-office work 5 days per week, with occasional remote-work flexibility.
Equity may include options or restricted stock units.
Health, dental, vision, life, and disability insurance.
401(k) retirement benefits with employer match.
Learning and wellness stipends.
Paid time off.