Senior Systems Engineer - ODD Definition and Automation

As a Sr. System Engineer (Data Analysis & Statistics Background), you will play a key role in evaluating and enhancing the safety and reliability of autonomous trucking systems. You will work with functional (FuSa) and behavioral safety (SOTIF) engineers, system engineers, data scientists, AI-ML engineers, and SW Devs to ensure that our autonomous system operates safely and effectively under all conditions.

Analyze and select specific data elements needed for all 6 layers as part of the PEGASUS framework. Based on this structured framework, generate comprehensive scenario-based requirements, and the testing, verification, and validation (V&V) for L4 autonomous driving. 

• Derive system requirement based on specific scenarios and use cases related to Operational Design Domain (ODD) for L4 applications

•  Apply system methodologies and data analysis to characterize the ODD to improve the vehicle requirements at the system level

• Selected scenarios and use cases based on ODD characterization

•  Generate Behavior Systems Requirements, Sub-System, and Component Requirements. 

• Work with system and safety engineers, map engineers and data scientists to decompose and improve the requirements

• Interact with functional safety and system engineers to ensure SOTIF targets are achieved in autonomous vehicle development.

• Lead data analysis and information extraction in our organization

• Interact with AI-ML engineers and SW Developers to ensure the safety of Torc solutions

• Communicate ODD characterization results to the product organization and other critical stakeholders to improve requirements and testing

• Develop verification and validation targets for known and unknown safety scenarios.

• Support SOTIF-related operational strategies, ensuring the safe deployment of autonomous vehicles.

• Collaborate with systems design and architecture teams to ensure SOTIF considerations are integrated into autonomous trucking specifications.

What You’ll Need to Succeed:

• Demonstrates competences and technical proficiencies typically acquired through:

• Master’s Degree in Computer Science, Computer Engineering, Statistics, Systems Engineering, or equivalent with 3+ years relevant experience.

• Bachelor’s Degree in Computer Science, Computer Engineering, Statistics, Systems Engineering, or equivalent with 6+ years relevant experience.  

• Strong knowledge of automotive, heavy-duty truck, or aerospace products and industries.

• Leverage data science and statistics to extract information from large data sets

• Collect data from different sources (including maps) to identify the elements needed for the 6-layer framework

• Transfer data into a new formats to make it more appropriate for analysis

• Creating new, experimental frameworks to collect data

• Building tools to automate data collection

• Strong analytical skills, with the ability to assess risks, derive safety requirements, and define verification & validation strategies.

• Excellent project management and leadership skills, with the ability to drive safety initiatives across cross-functional teams.

• Highly organized and capable of handling multiple projects in a fast-paced, evolving environment.

• Strong interpersonal and communication skills, with the ability to collaborate effectively across engineering teams and leadership.

• Detail-oriented, self-motivated, and able to work independently while also leading discussions and influencing stakeholders.

• Comfortable working in an environment of ambiguity and rapid change, with the ability to quickly adapt and make informed safety decisions.

• Ability to ethically handle sensitive and confidential information with impartiality and professionalism.

Bonus Points! 

• Understanding of AI-ML techniques

• Solid knowledge of multivariable statistics and Bayesian Methods

• Working knowledge of Bayesian Networks

• Experience is SW development and knowledge of C++, Python, MATLAB/Simulink

• Working knowledge of Jama, CAMEO, and JIRA

• Experience in SAFe AGILE environments

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. 
Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. 

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.