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Serve as the technical lead for customers evaluating and integrating Applied Intuition's vehicle intelligence tooling. Lead demos, POCs, and integration workshops; support CI/CD and SIL/HIL/VIL validation pipelines; design data flywheels, scenario-based testing, and automated validation; translate customer feedback to product teams and manage technical workstreams across stakeholders.

Drive end-to-end systems engineering for automotive ADAS/parking: define/manage requirements, generate safety concepts, implement V&V strategy, map regulations into requirements and tests, track KPIs across simulation and real-world data, and work directly with customers.

Research intern working on reinforcement learning for large-scale self-play, VLA post-training, and neural simulation applied to autonomous driving and robotics; collaborate with scientists and engineers toward top-tier publications and deployable autonomy solutions.

Lead and scale end-to-end people programs across the employee lifecycle. Build documentation, processes, and compliance frameworks. Partner cross-functionally, analyze people data to improve programs, and own HR policy development and interpretation.

Lead hardware integration for autonomous vehicles: build, test, and maintain fleet hardware; design and install sensors and proof-of-concept systems; perform bring-up, shakedown testing, build test benches, troubleshoot electrical/computer/sensor systems, document procedures, and minimize vehicle downtime while ensuring safety.

Lead and grow an engineering team building data quality systems, intelligent labeling workflows, and large-scale data mining to surface edge cases. Drive integration of foundation models, set technical direction and roadmaps, partner with research and infrastructure teams, and hire and mentor engineers to scale high-fidelity labels and accelerate ML iteration for autonomy.

Design and implement single- and multi-target detection, tracking, and decentralised multi-agent sensor-fusion and state-estimation algorithms for unmanned autonomous systems; productionize algorithms into robust deployable software and collaborate with cross-functional teams.

Provide first-line technical support, manage user onboarding/offboarding, design and build scalable corporate IT infrastructure, troubleshoot systems/networks/hardware/software, and escalate complex issues to senior staff.

Build and productionize scalable backend services, APIs, and AI workflows to connect requirements, modeling, validation, and test data for autonomous vehicle programs. Implement traceability, versioning, dashboards, and KPIs, refactor prototypes into certifiable systems, and collaborate with systems engineering, safety, and autonomy teams to support compliance and validation at scale.

Build and ship shared AI infrastructure, agent frameworks, and tooling; partner with product teams to productionize LLM and agentic features; own GenAI best practices for architecture, safety, evaluation, and deployment; develop agentic systems and AI SRE tooling; engage with customers to shape roadmap and demos.