Design and validate electrical platforms and wiring harnesses for autonomous trucks, from sensor and computing architecture through vehicle integration, production readiness, troubleshooting, and regulatory validation.
Coordinate autonomous truck fleet dispatch, personnel and mission schedules, and real-time operations across testing sites, partnering with operations and engineering teams to support safe, efficient mission execution.
Lead validation and verification of autonomous-driving software through closed-course and field testing, creating test plans, diagnosing system issues, and improving testing operations with tooling and documentation.
Design and train Vision-Language-Action models for autonomous driving, owning workstreams from data and architecture through large-scale training and on-vehicle validation, and optimizing models for onboard deployment.
Own Japan-based customer programs as the primary partner contact, coordinating engineering, product, and operations teams while managing plans, milestones, risks, and bilingual stakeholder reporting.
Develop quantitative safety and comfort metrics, automate simulation-based verification, and investigate software failures across autonomous vehicle perception, prediction, planning, and control systems.
Develop motion-planning algorithms for autonomous trucks, translating robotics and machine-learning techniques into production systems that make safe, smooth decisions and trajectories in complex, uncertain driving situations.
Build and optimize the production runtime for machine-learning-based autonomous vehicle planning, integrating models into safety-critical systems and improving inference performance, reliability, and observability.
Design and deploy reinforcement-learning-based behavior planning for autonomous trucks, owning model training pipelines and improving performance and generalization across driving scenarios.
Develop and deploy machine learning planning systems for autonomous vehicles, owning model design, evaluation, and production integration to improve trajectory quality, safety, robustness, and runtime efficiency.
Own the end-to-end evaluation loop for autonomous driving, building fleet-scale performance metrics and data pipelines, analyzing geospatial behavior, supporting release decisions, and automating issue triage.
Build and scale simulation infrastructure for autonomous vehicles, using AI-driven analysis and data to improve simulation fidelity, validate autonomy performance, and support critical engineering milestones.
Lead mapping and localization engineering for autonomous trucks, developing sensor-fusion algorithms, HD map systems, and robust localization that supports safe operation in complex driving environments.
Design and optimize Bird’s Eye View perception models that fuse camera, LiDAR, and radar data, advancing robust, scalable 3D scene understanding for autonomous driving systems.
Develop methods to mine, rank, and retrieve valuable fleet data for autonomous-driving training and evaluation, then deliver scalable pipelines and search tools used by autonomy and ML engineers.
Own and evolve the compute platform behind large-scale data processing, simulation, and model training by improving Kubernetes reliability, enabling self-service workloads, and building reusable batch and workflow capabilities.
Build the data infrastructure that makes autonomous-driving fleet data reliable and accessible, spanning high-throughput vehicle recording, transfer and validation, data formats, storage, replay, analytics, and machine learning.
Build PlusAI’s social and digital presence by creating engaging content, growing audiences and communities, and translating complex technology and business topics into clear stories across platforms.
Build PlusAI’s retail investor relations function from the ground up, growing an informed investor community through compelling content, real-time engagement, shareholder analytics, and clear sentiment reporting to the CFO.
Integrate and optimize on-vehicle autonomous driving systems by developing AUTOSAR communication and diagnostics, bringing up vehicle platforms, troubleshooting issues, and validating embedded software through testing.
Leads validation and verification of autonomous driving software through end-to-end test planning, hands-on vehicle testing, troubleshooting, and tooling that improves testing operations.
Build and maintain scalable data pipelines and infrastructure, develop analytics tools and reports, uncover trends in complex datasets, and support stakeholders’ data analysis and reporting needs.
Build and maintain simulation frameworks and machine-learning workflows that generate and validate autonomous-vehicle scenarios, supporting safety evaluation across autonomy systems and enabling partner teams’ testing workflows.
Develop and improve autonomous-truck motion planning and control through learning-based algorithms, vehicle models, data pipelines, and systematic simulation and road testing.
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