Architect and extend our next generation core simulation technologies (e.g. world engine,  interfaces, scheduler, agent frameworks).

Drive the integration of core simulation technologies into solutions or workflows, ensuring end user requirements are met.

Analyze simulation results to identify gaps between simulated and real-world performance. Prioritize improvements in the core simulation and integration software.

Partner with ADAS autonomy, integration, and release teams to improve validation of ADAS software.

Help set the team roadmap to support the growing landscape of ADAS customers and data sources.

Demonstrate good design practices; alignment with stakeholders before, during, and after implementation is essential.

Propose and advocate for modern technologies and methodologies that can drive innovation and performance.

Receive decomposed customer-level requirements, or  conceptual and historical design studies and experiments to generate test methods. Support test driven development activities to help elicit requirements and feed results back to definition and functional creation teams. 

Support definition and execute the end‑to‑end test strategy – coordinate testing levels, modalities (SIM, Closed Course, On-Road, SIL/HIL), ensuring our test approach aligns with Product and customer level requirements and roadmap.

Ensure robust verification of system requirements and proxy validation of customer requirements – own the frameworks, ownership model, and RACI for validation so that system, software, and customer‑level needs are consistently tested and traceable - executing 

Set quality gates, metrics, and reporting for V&V outcomes – define performance and quality metrics, acceptance criteria, and reporting that feed Release decisions, enabling data‑driven releases and continuous improvement.

Represent V&V in cross‑functional and external forums – act as the accountable voice of V&V with Product Delivery leadership, other AD/ADAS functions, and TMC, communicating status, risks, and trade‑offs to support safe, predictable product integration and launch.

8+ years experience with software systems verification and validation in a production setting, as an individual contributor or team lead (in combination)  

Proven ability to launch software systems to production with a demonstrated track record. Point to production program launches - inside or outside of the automotive industry - where your team’s work played a critical role in ensuring the system launched to market with high quality. 

Demonstrated ability to build teams, especially with respect to quality-associated deliverables. Showcase how you developed and implemented foundational standard operating procedures leading to higher quality team output. 

Strong communicator, especially in a global team environment. 

Automotive ADAS Domain experience is considered a plus, but not required. 

Lead adoption and integration of machine learning techniques in simulation subsystems and workflows (e.g. scenario creation, reactive agents and sensor/vehicle/intersection/world modeling).

Architect and extend our next generation core simulation technologies (e.g. agent frameworks,  scenario engine, sensor simulation).

Partner with ADAS teams to improve the development and evaluation of ADAS software.

Help set the team roadmap to support the growing landscape of ADAS customers and use cases.

Demonstrate good design practices; alignment with stakeholders before, during, and after implementation is essential.

Bachelor's or Master's degree in Computer Science, Engineering, or a related field highly preferred.

5+ years of relevant work experience.

Experience with machine learning frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred).

Experience in machine learning workflows, such as data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization

Strong programming skills in Python, Rust or C++.

Proven track record crafting well-designed, impactful solutions within allotted time and resource constraints.

Ability to think, design, and code for both the user’s and simulator developer’s perspectives.

An infectious self-driven passion for solving complex problems while learning new techniques and technologies!

Familiarity with recent breakthroughs in machine learning (e.g. foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures).

Experience with building real-time systems (a requirement of simulations for driver assistance and hardware in the loop scenarios).

Experience with build systems, continuous integration, and/or continuous deployment (CI/CD).

Experience in the automotive and/or self-driving autonomy domain.