Top Tech Jobs & Startup Jobs in Austin, TX

As a Machine Learning Engineer, you will design, train, and deploy ML models for motion planning, develop data pipelines, and integrate models for real-time use in autonomous vehicles.

Lead development of Avride's control system by architecting and shipping Model Predictive Control (MPC) solutions in modern C++, identifying vehicle dynamics parameters from real-world data, profiling for real-time performance, and providing technical leadership, code review, and mentorship to a small controls team while aligning with Planning and Hardware.

Analyzes autonomous-vehicle data and driving scenarios to validate dataset quality, identify edge cases and coverage gaps, monitor quality metrics, and investigate anomalies. Reviews annotation batches, maintains dashboards and reports, and automates validation and testing workflows using Python, Pandas, and ClickHouse. Collaborates with product and engineering teams to improve annotation efficiency, testing processes, and data quality.

Build and architect React/TypeScript web applications powering internal engineering tools (simulation, fleet tracking). Collaborate with simulation, analytics, and ops teams to integrate systems, shape APIs, and deliver performant, reliable UIs that enable diagnostics, scenario mining, and fleet configuration.

Own and architect the top-level safety case for autonomous vehicles, decompose claims and required evidence against UL 4600 and aligned standards, coordinate cross-pillar evidence production, maintain traceability tooling, prepare for third-party assessments, and report safety case maturity and gate readiness to leadership.

The Senior Brand Designer will develop and maintain Avride's visual identity, design marketing materials, uphold design standards, and collaborate on campaign concepts. They will influence visual communication for a tech-focused brand.

Design, develop, and maintain low-latency device drivers and sensor pipelines for cameras, LiDAR, radar, IMU, GNSS and other sensors. Implement timestamping, filtering, preprocessing, and sensor-health analysis. Collaborate with embedded, perception, and localization teams to integrate and debug hardware/software, optimize performance, and act as the sensor-domain expert guiding solutions and troubleshooting.

Develop and implement on-board localization and cloud mapping algorithms, optimizing rover localization accuracy and cloud mapping processes in challenging environments.

The ML Platform Engineer will build scalable architecture for ML training workloads, optimize system performance, and collaborate with teams for enhanced efficiency on Kubernetes.

Own and harden on-board networking and Linux platform for autonomous vehicles: design fault-tolerant internal networks, implement PTP/gPTP time synchronization, tune Linux networking (NIC buffers, offloads, NAPI), build connectivity daemons (Go/Python) for multi-carrier cellular bonding, integrate networking with embedded Linux on x86_64 and ARM64, and build observability for fleet connectivity.