Role Description The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, verifying and validating the autonomy stack, and defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year. We are looking for a passionate, self-starting engineering leader to lead the AV Behavior Understanding and Evaluation team within the SRP organization. This team defines the standards for safe, comfortable, and assertive autonomous driving. We bridge the gap between systems engineering and real-world performance by decomposing the Operational Design Domain (ODD) into actionable competencies. The team owns the behavior definition, actionable driving policies backed by tests, and acceptance criteria derived from standards and human benchmarks. The team works closely with the autonomy teams on both target setting and validation. We are seeking a hands-on Principal Engineer Team Lead to drive the design, evaluation, and scaling of these systems through data-driven design backed by structured and large-scale assessment in simulation and on the road. You will lead a high-performing team to transform complex data into measurable progress toward a safer, smarter transportation future. What You'll Do - Design the System Behavior: - Decompose ODD requirements into system and subsystem behaviors and interfaces to ensure vehicle capabilities meet product requirements. - Characterize the performance target against parameters used to define AV capabilities to provide nuance in performance evaluation. - Develop actionable policies and measurable targets: - Convert legal and industry policy narratives to mathematical and/or specific requirements that the autonomy teams can implement. - Leverage human benchmark and industry standards to establish measurable acceptance criteria for system readiness. - Drive Evaluation Strategy: - Advance our performance assessment framework by defining key metrics and reward functions. - Derive Launch Criteria and Driving policy and strategically plan and execute testing campaigns leveraging advanced structured and large scale simulation, closed-course tracks, and on-road data. - Lead and Scale: - Mentor and grow a high-performing engineering team. - Foster a culture of technical excellence, scientific rigor, and data-driven decision-making. - Cross-Functional Collaboration: - Partner with Autonomy, Infrastructure, and the other Systems teams to drive design improvements. - Ensure features generate a net positive effect on system safety, comfort, and assertiveness and meet our launch criteria. - Data exploration: - Leverage data science techniques and existing infrastructure to understand the problem space and engage with development teams to drive resolution in close collaboration with System Performance. - Incorporate Bleeding Edge technology: - Leverage a combination of learning methods and metrics along with classical metrics to stretch the horizon of performance evaluation. Qualifications - Bachelor's degree and 7+ years of experience in Systems Engineering, Autonomous Systems, or Robotics, with deep expertise in one and working knowledge of the others. - Or Master’s degree/PhD and 5+ years of experience. - 3+ years of experience leading and scaling data-driven evaluation programs for autonomous driving or safety-critical emerging technologies. - A hands-on technical leader with a proven track record of growing small, high-performing teams. - Demonstrated track record in decomposing ODD requirements into vehicle capabilities, driving behavior logic, and defining measurable acceptance criteria. - Expert at leveraging large-scale simulation, track, and road data to extract actionable technical insights that drive resolution with development teams. - Proven track record of building consensus and driving alignment across multidisciplinary teams—spanning Autonomy, Infrastructure, and Operations—by leveraging technical influence over organizational authority. - Strong foundation in statistical methodology, Data Science, and scientific rigor. - Proficiency in Python, SQL, and data visualization techniques. - Excellent communication skills; capable of articulating complex concepts to technical peers and executive leadership alike. - Self-starter with a proactive mindset for driving ambiguous projects to completion. Ideally, You Also Have - Master’s degree in Systems Engineering, Autonomous Systems, or Robotics. - Familiarity with SOTIF, ISO 26262, UL4600, AVSC Behavior competencies and other industry standards. - Experience shaping product roadmaps. - Experience establishing and leveraging industry benchmarks as well as human naturalistic driving behaviors to improve autonomous driving. - Familiarity with Reinforcement Learning (RL). - Experience collaborating within agile environments and global, distributed teams. - Experience with Industry standards and establishing human benchmarks. - Specialized expertise in creating expansive datasets. - Experience collaborating in an agile development environment. Benefits - Medical, dental, vision insurance. - 401k with a company match. - Health saving accounts. - Life insurance. - Pet insurance. - And more. Salary Range $200,000 — $275,000 USD

• Support all race, test, simulator and rig activities • Work in conjunction with other engineers and drivers to optimize performance on track • Provide pre & post event simulation, analysis and key performance metrics of tyre performance in race and test events • Assist in developing tyre physics understanding and in conjunction with tyre modelling engineers to support vehicle performance analysis and development • Ensure ongoing validation and correlation of the tyre models to track and rig data to ensure robust validation of simulation results • Research and use appropriate technologies to ensure the continuous development of our models to meet the engineering requirements of the Team • Interact across the entire Team to provide methodologies, tools and solutions to support objective technical decision making

• Support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem. • Design, implement, and manage Identity and Access Management (IAM) solutions, ensuring secure authentication and access control across cloud and on-premises environments. • Enforce Zero Trust Architecture (ZTA) principles and role-based access control (RBAC) policies to protect mission-critical systems. • Integrate IAM solutions with Microsoft Entra ID (formerly Azure Active Directory), Public Key Infrastructure (PKI), and Common Access Card (CAC) authentication mechanisms. • Oversee IAM automation, ensuring streamlined provisioning and de-provisioning of user roles and permissions. • Submit the Identity & Access Management Compliance Report, detailing system configurations, access logs, and compliance status.

Role Description We are looking to strengthen our team for a MLE (Speech Tech, ASR)! Qualifications - 3+ years of hands-on experience in speech recognition or a closely related field. - Proficiency in Python and deep learning frameworks (especially, PyTorch). - Strong understanding of the state-of-the-art automatic speech recognition techniques and models. - Experience with Streaming ASR Models (e.g., Conformer). - Strong understanding of recognition improving techniques such as beamsearch and language modeling. - Familiarity with ASR evaluation techniques. - Knowledge of signal processing, statistical modeling, and language structure. - Nice to have: MLOps experience, including MLFlow or similar experiment tracking systems. - Familiarity with low-latency audio streaming and optimization techniques for deploying efficient real-time processing systems. - Hands-on experience with Triton Inference Server and TensorRT for production model deployment. - Proficiency in building ML backends and deploying APIs. Requirements - Design and optimize ASR models to ensure that we recognize client’s speech as accurate as possible. - Collaborate closely with product managers and engineers to integrate ASR tech, making it seamless and intuitive for users. - Partner with data teams to build efficient audio data pipelines, from preprocessing to model training. - Regularly update and refine ASR models to adapt to various domains and dialects, enhancing user satisfaction and responsiveness. - Keep up-to-date with the latest ASR advancements, bringing in innovative techniques and tools to keep us at the forefront of voice-assisted banking. - Rigorously test and validate models to meet strict standards. Benefits - The team has built award-winning AI products for tech corporations' devices, voice assistants, products that are actually in the world. - Cutting-edge tech stack: Speech Technologies, NLP, Generative AI (LLMs, diffusion models), voice-first agentic architecture with privacy-first and on-premises deployment. - High engineering bar and real ownership - the team cares about what actually works in production, not what looks good in a demo, and you'll see the impact of your work directly. - Fast career progression - a senior-heavy team and a high volume of real problems means you grow faster than you would anywhere else. - Startup pace with enterprise stability - real clients, real revenue, no bureaucracy. - Fully remote across Europe. - 21 vacation days + public holidays + 5 sick days. - Private English lessons via Preply. - Company-paid subscriptions to top AI tools (ChatGPT, Claude, Cursor, and others).