Motional

Full-stack Engineer

• 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

Staff Engineer

• 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 strategies, progress and challenges to executive leadership

Principal Engineer

• Build, lead, and manage a high-performing team of data and infrastructure engineers focused on building out Motional’s Data Stack
• Define team goals, priorities, and roadmap in alignment with company objectives
• Provide technical guidance, mentorship, and career development opportunities to team members
• Define the technical vision and strategy for storing metrics and generating ML datasets for large computer vision and behavioral models
• Identify and evaluate cutting-edge technologies and methodologies for speeding up data loaders for training, ingestion of metrics, and querying of large datasets
• Collaborate closely with ML research, ML Training platform, and data engineering teams to understand their needs and integrate solutions seamlessly
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders

Staff Technical Lead Manager – AI Data Engine

• Deep-dive into complex issues within the Planning and Controls stack reported by the triage team
• Parse logs and replay simulation data to find the 'why' behind anomalous vehicle actions
• Own the deployment of software fixes
• Lead the development, testing, and deployment when a business need arises for an immediate solution
• Identify improvements in existing workflows
• Develop internal tooling and scripts to expedite log analysis, automate common patterns, and improve the efficiency of the entire team
• Act as the technical liaison between teams to ensure alignment between on-road issues and current development work

Senior Software Engineer, Autonomy Actions Sustaining

• Collaborate closely with data mining, ML researchers, and other data platform teams.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Design and build the next generation of data curation, mining, and search applications.
• Mentor junior engineers and peers on best practices and adoption strategies.

Senior Software Engineer – AI Data Applications

Systems Engineer

• Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
• Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
• Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
• Optimize robust data loading pipelines that maximize training throughput.

Machine Learning Systems Engineer

Machine Learning Engineer

• Define Technical Strategy &amp; Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems.
• Architect System-Level Solutions: Own the system-level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real-time inference across GPU/CPU clusters.
• Drive Cross-Functional Execution: Lead multi-person projects to completion across teams. Influence partner teams' technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment.
• Elevate Engineering Excellence: Establish department-wide standards for ML system design, code quality, testing, and deployment.
• Operate as a Generalist Expert: Apply a broad toolkit of ML techniques to solve complex, ambiguous problems.
• Mentor and Lead: Act as a role model and technical go-to person. Coach Senior and junior engineers, lead architectural reviews, and elevate Motional’s engineering culture.

Staff Machine Learning Engineer

• Spearhead efforts for the Perception subsystem of our autonomy stack
• Close the safety case for the perception subsystem
• Collaborate with autonomy and systems engineers to establish problem taxonomies and identify critical performance covariates
• Influence requirements from the perspective of problem understanding, covariate coverage, and testing capabilities/challenges
• Validate the test strategy and provide early feedback to developers
• Create and automate reporting dashboards
• Be a bridge between Perception and the Systems Readiness and Performance organization
• Advocate for and adopt common processes, technology, and terminology

Principal Engineer, Verification & Validation Lead

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.

Senior Engineer, Autonomy ML Systems

• Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR).
• Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines.
• Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows.
• Monitor Production Performance: Help build and maintain dashboards to monitor model health.
• Learn and Apply Best Practices: Follow software engineering standards for ML code.
• Collaborate Across Teams: Work closely with senior engineers and machine learning engineers.