Motional

• Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs. • Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference. • Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios. • Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs. • Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking. • Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains. • Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events. • Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks.

Role Description We are seeking an experienced and visionary Principal Technical Lead Manager to build and lead our new AI Data Application team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating our ML dataset generation and data search applications. The ultimate goal is to drastically reduce the development cycle for new pipelines, ML models and get us operationally prepared for a driverless future! You will be a hands-on leader, blending deep technical expertise in data systems and infrastructure with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvements. What You'll Be Doing - Team Leadership & Management: - Build, lead, and manage a high-performing team of full stack web engineers. - Define team goals, priorities, and roadmap in alignment with company objectives. - Provide technical guidance, mentorship, and career development opportunities to team members. - Technical Strategy & Execution: - Define the technical vision and strategy for building services and web platforms for storing and searching metadata and forming datasets. - Define AI adoption strategy for frontend codebase and UX projects to speed up development and time to market. - Identify and evaluate cutting-edge technologies and methodologies for querying through datasets stored in various types of databases (think images in vector store, metadata in Postgres, etc) and APIs owned by several teams across the company. - Cross-functional Collaboration: - Collaborate closely with data mining, ML researchers, and other data platform teams to understand their needs and integrate solutions seamlessly. - Communicate complex technical concepts and strategies to both technical and non-technical stakeholders. Qualifications - BS or MS in Computer Science or related field - 8+ years of professional experience in building web applications - 3+ years of experience in a technical lead or management role - Extensive experience with building web applications for search and data curation needs. - Extensive experience with API and query federation technologies such as GraphQL or AWS Athena. Requirements - Strong programming skills in Typescript and Python. - Strong knowledge of modern frontend technologies such as React. - Strong knowledge of building REST and gRPC based services, ideally in Python. - Prior experience with building web applications for engineering or machine learning needs. Bonus Points (not required) - Prior experience in autonomous vehicles (AV) is a plus. - Prior experience with Bazel based build systems. - Prior experience with developing frontend workflows using LLMs. Benefits - Medical, dental, vision - 401k with a company match - Health saving accounts - Life insurance - Pet insurance - And more Salary Range $240,000 — $330,000 USD Company Description Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more. - Our journey is always people first. - We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. - Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move. - We’re creating first-of-its-kind technology that will transform transportation. - Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives.

• Lead the development of evaluation frameworks for the autonomous system • Collaborate closely with Functional Safety and Systems Engineering teams • Ensure evaluation metrics are reliable enough to inform safety cases • Monitor the reliability of evaluation metrics and incoming performance data over time • Drive our approach to performance analysis using data-backed statistical methods • Develop new statistical analysis methods to analyze AV performance data • Partner with triage operators to turn raw disengagements into scenarios • Use fleet and evaluation data to identify edge cases in an automated manner • Build confidence in the evaluation framework through data-driven insights • Establish correlation between on-road and simulation data • Make sense of large datasets to drive insights • Establish a self-service model for developers • Develop new metrics, interpret trends, and investigate anomalies • Collaborate with developers to drive action based on these results • Serve as an advisor and influence collaborators across multiple teams • Mentor and collaborate with fellow engineers • Introduce the use of ML methods for performance evaluation

• Lead the development of evaluation frameworks for the autonomous system • Collaborate closely with Functional Safety and Systems Engineering teams • Monitor the reliability of evaluation metrics and performance data • Drive our approach to performance analysis using data-backed statistical methods • Build confidence in the evaluation framework through data-driven insights • Establish correlation between on-road and simulation data • Establish a self-service model for developers • Mentor and collaborate with fellow engineers

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

Role Description We are looking for a Software Engineer to join our ML Infrastructure: Dev Enablement Team. Our mission is to build a frictionless development environment that empowers our researchers and engineers to rapidly innovate on deep learning models for autonomous driving. We manage a high-scale Cloud Development Environment (CDE) platform that provides standardized, high-performance workspaces for ML development. In this role, you’ll spearhead high-impact initiatives: - Designing multi-cloud setups to maximize GPU availability - Driving deep-level model optimization - Building next-generation Agentic AI toolings You will play a pivotal role in ensuring our training ecosystem remains cutting-edge, resilient, and highly efficient. What You’ll Be Doing - Build Agentic AI Tooling: Design, develop, and enhance Agentic AI tools and systems to automate workflows, streamline the ML lifecycle, and empower developer productivity. - Scale Core Infrastructure: Drive the continuous development of our core ML infrastructure and existing CDE platform, leveraging Kubernetes to build robust, high-scale distributed solutions. - System-Level ML Optimization: Partner closely with ML Researchers to profile and optimize distributed training jobs (PyTorch/DDP) and data pipelines. Focus on resolving system-level bottlenecks—such as data loading (I/O), memory management, and network communication overhead—to maximize GPU utilization and training throughput. - Collaborate Cross-Functionally: Partner with ML engineers and data scientists to understand their complex needs, bridging the gap between underlying infrastructure and model development. Qualifications - BS or MS in Computer Science or related field - Strong knowledge of software engineering principles and distributed systems - Strong proficiency with Python or Go or C++ - Experience with building on AWS services or other Cloud platforms and container orchestration using Kubernetes - Experience with the various stages of the ML development lifecycle Bonus Points - Hands-on experience with ML model profiling and performance optimization for distributed training - Experience managing or working with high-performance compute resources (GPUs) - Experience with ML frameworks such as PyTorch or Ray - Experience building, integrating, or enhancing Agentic AI systems and LLM-driven developer tools Benefits - Medical, dental, and vision insurance - 401k with a company match - Health saving accounts - Life insurance - Pet insurance - Additional forms of compensation such as bonuses or company equity Salary Range $123,000 — $163,500 USD

• Work on large-scale solutions for mining challenging driving scenarios to boost learned model performance across various autonomous driving tasks. • Collaborate with ML (Machine Learning) infrastructure teams and contribute to workflows for continuous learning through iterative mining, error analysis, training and deployment. • Research and develop methods for extracting uncertainty and informativeness indicators to automatically mine for challenging scenes and analyze model performance. • Provide statistical depth and insights on model uncertainty, generalization and robustness. • Conduct deep learning experiments and write technical reports. • Provide guidance to junior researchers on research projects and design document reviews. • May work remotely from any U.S. state.

• Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). • Implement scalable data preprocessing and augmentation pipelines. • Help develop embedding-based search tools and 'active learning' workflows. • Help build and maintain dashboards to monitor model health, data drift, and system performance. • Follow software engineering standards for ML code and participate in code reviews. • Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable engineering solutions.

Role Description The AV Behavior Design and Evaluation Team is responsible for owning the design and assessment of the AV behavior utilizing the concept of AV behavior competencies. The team relies on systematic decomposition of AV behavior along with data driven assessment utilizing data from on-road and simulation test modalities. We are responsible for building and operating robust, large-scale evaluation systems, alongside sophisticated simulation workflows and insightful diagnostic tools. By combining expert human judgment with advanced data driven techniques, we evaluate the system behavior performance. As the team is looking to scale to support more and more behavioral competencies, we are looking for passionate Engineers to help build a robust framework to leverage the best of agile systems engineering and data driven performance assessment to achieve our ambitious goals in scaling our system design and evaluation processes. We are looking to work with people who are driven to design robust systems and transform complex data into measurable progress toward a safer, smarter transportation future. This person will get to build relationships with the team as well cross-functional across organization to help build a cohesive understanding AV performance as applicable to the Behavioral Competencies. - Propose behavioral expectations on AV capabilities - Support standardization of metrics used in performance evaluation for AV Capabilities to ensure consistency - Effectively utilize existing metrics and propose the need for new metrics to evaluate AV performance in large scale simulation testing - Propose soft/hard targets for metrics using statistical methods and back them up with driving data - Propose and implement ideas to analyze simulation, resimulation and public road testing results for stakeholders in Systems, Autonomy, Safety etc. - Deliver strategic insights and recommendations on projects regarding scenario-based testing - Build meaningful visualizations and templates for the team to utilize - Focus on automating result analysis processes and gaps, removing manual processes where applicable - Support the development, execution, and analyses of test strategy for features validation - Communicate test results to development teams and management and facilitate resolving of technical issues Qualifications - Bachelor's degree and 2 years of experience in Engineering, Computer Science, Data Science OR equivalent experience in relevant industry - Strong understanding of Autonomous Vehicle architecture and functions of key subsystems such as perception, planning, prediction etc. - Experience with analyzing simulation and real world data for robotic systems, preferably autonomous vehicles - Fluency in SQL or similar languages - Fluency in data visualization techniques - Experience in building python based projects for data analysis and insights - Excellent interpersonal skills to build relationships with other teams - Excellent communication skills; effective in communicating complex concepts and driving resolutions - Self-starter who is motivated to set and achieve goals and takes initiative to drive ambiguous tasks/projects to completion Requirements - Bonus Points (not required): - Masters degree in relevant field - Experience using simulation tools - Experience in evaluating Autonomous Driving Behavior using large scale data - Familiarity with AV Behavior evaluation standards and best practices Benefits - Medical, dental, vision - 401k with a company match - Health saving accounts - Life insurance - Pet insurance - And more Salary Range $149,000 — $198,500 USD

• Define and execute motion planning and prediction projects that improve our self-driving vehicles’ capability to safely, comfortably and legally navigate complex traffic scenarios • Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning • Productionize and deploy solutions onto autonomous vehicle fleets • Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products’ on-road performance • Communicate progress and challenges to leadership