Applied Intuition
Robotics · Autonomous-vehicle software
Robotics · Autonomous-vehicle software
Applied Intuition currently has 63 active AI-related roles in our index. The most common open titles are: Applied Perception Engineering Lead (2), Autonomy Integration Software Engineer, C++ Software Engineer (Autonomous Systems), C++ Software Engineer - Autonomy/Physical AI, Data & ML Pipeline Software Engineer. Most positions are in Engineering and Research.
Applied Intuition's active AI hiring is concentrated in: agents (32%), data (19%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Applied Intuition is hiring AI talent in: United States (58 roles), South Korea (2 roles), United Kingdom (1 role).
Job postings at Applied Intuition most frequently reference: model serving, multimodal, inference infra, agent orchestration, vision.
In the past 30 days, Applied Intuition has posted 10 new AI-related roles. That is a +25% change versus the prior 30 days (8 → 10).
| Title | Stage | AI score |
|---|---|---|
| Research Engineer - AI/RL Infrastructure Research Engineer focused on building and operating large-scale ML training and evaluation infrastructure for physical AI systems, including autonomous driving and robotics. The role involves orchestrating GPU clusters, developing benchmarking and data pipelines, and enabling distributed training across cloud environments. | DataEval Gate | 9 |
| Engineer Manager - ML Data and Evaluation, Self-Driving Systems Engineering Manager to lead the data and evaluation layer for E2E autonomy models in robotics, covering data enrichment, dataset curation, evaluation infrastructure, and closed-loop systems. The role focuses on accelerating model iteration speed and ensuring the quality of data and evaluation for safety-critical systems. | Data |
| 8 |
| Software Engineer - E2E Autonomy Software Engineer role focused on building ML tools and infrastructure for end-to-end autonomy research and production in self-driving vehicles. Responsibilities include scaling training, managing datasets, and supporting GPU compute and eval systems. | DataServe | 8 |
| Software Engineer - Axion Data Engine and ML Ops Software Engineer role focused on building the data engine for training perception models, including edge applications and cloud data ingestion pipelines. The role involves optimizing ML model execution on edge and cloud, developing MLOps tooling, and integrating foundation models for data automation. | DataPost-train | 7 |
| Data & ML Pipeline Software Engineer Software Engineer focused on building and maintaining large-scale data processing pipelines (ETL) for ingesting and curating driving datasets, designing systems that automate data selection, labeling, training, and testing loops, and developing infrastructure to close the loop between real-world test results and new model deployments for autonomous vehicles. | DataPost-train | 7 |
| Engineering Manager - Data Intelligence Engineering Manager for Data Intelligence team focused on producing, curating, and leveraging high-quality data for autonomy development. Responsibilities include managing engineers, prioritizing data quality systems, labeling workflows, and data mining, and integrating foundation models to enhance these processes. | DataPost-train | 7 |