Jobs at Applied Industrial Technologies

Build and own an onboard live-map estimator for autonomous vehicles, fusing HD map priors with live perception in real time. Develop map change detection, trust semantics, evaluation and regression pipelines, and degraded-mode behavior. Ship modern C++ estimation software on embedded compute while defining interfaces with planner and consumer teams. Extend the system into fleet-based map freshness and correction pipelines.

Own the onboard live-map estimator for autonomous vehicles by fusing HD map priors with perception and sensor data. Develop real-time C++ estimation and map-change detection, define planner trust and degraded-mode semantics, and build evaluation, ground-truth, metrics, and regression pipelines. The role requires production state-estimation expertise, embedded performance optimization, uncertainty modeling, system interface definition, and collaboration with consumer teams. Nice-to-have experience includes live mapping, HD map semantics, factor-graph frameworks, integrity monitoring, and advanced study in estimation or SLAM.

Coordinate phone, virtual, and in-person interviews; improve recruiting processes and candidate experience; evaluate recruiting strategies; support interview training, funnel analytics, enablement content, university career fairs, and industry recruiting events. Partner with sourcers and recruiters in a fast-paced, high-growth environment.

Reviews and validates autonomous vehicle test-drive data for completeness, accuracy, and relevance. Identifies anomalies, supports data annotation and labeling for machine learning, develops automation scripts for verification, documents quality standards, reports data quality metrics, and collaborates with engineering teams to improve collection methods and verification workflows.

Develop and evolve compensation programs, advise business leaders on compensation strategy, lead benchmarking and market analysis, support compensation reviews and job architecture, and create scalable processes. The role requires expertise in cash and equity compensation, pay equity, leveling frameworks, financial forecasting, stakeholder management, and AI-enabled people solutions across functions and geographies.

Integrate and improve commercial robots for industrial autonomy. Design and fabricate mounts, fixtures, enclosures, retrofit kits, and end-effectors; integrate mechanical, electrical, sensing, compute, and power systems; diagnose faults; validate and document hardware; maintain lab systems; and support robot-cell safety. Candidates need practical mechatronics experience, CAD and fabrication skills, electrical troubleshooting ability, and documentation expertise. Experience with industrial robots, safety systems, teleoperation hardware, Python, ROS 2, or CAD-to-URDF workflows is beneficial.

Lead technical recruiting for software and machine learning engineering teams. Develop hiring strategies, partner with engineering leadership, manage structured interviews, improve recruiting systems, analyze funnel metrics, mentor recruiters, and deliver strong candidate experiences. The role requires recruiting specialized technical talent, including autonomy, robotics, defense, embedded systems, or Physical AI professionals, in a fast-growing, in-office environment.

Build and manage technical talent pipelines across autonomy, AI/ML, embedded systems, and software engineering. Develop research-driven sourcing and talent-mapping strategies, partner with hiring managers to define candidate profiles, collaborate with recruiters to support candidate experience, and use market research and data to improve sourcing efforts.

Manage a full-lifecycle technical recruiting desk for engineering roles. Responsibilities include sourcing specialized talent through LinkedIn and creative channels, building targeted recruiting campaigns, partnering with leadership using recruiting metrics, improving workflow efficiency with AI tools, and delivering an exceptional candidate experience while strengthening the employer talent brand.

Source technical talent for autonomy, ML/AI, embedded systems, and software engineering roles. Build and manage candidate pipelines, develop research-driven sourcing and talent-mapping strategies, partner with hiring managers, collaborate with recruiters, and use market research and data to improve sourcing approaches. The role requires strong communication, organization, relationship-building, and technical recruiting experience.

Develop and execute recruiting strategies for software and ML engineers, partnering with engineering leaders on hiring plans and talent strategy. Lead structured interviews, improve recruiting systems and processes, provide data-driven funnel insights, manage complex searches, mentor recruiters, and deliver an excellent candidate experience. The role focuses on scaling specialized technical teams in a fast-growing physical AI company.

Build and optimize edge and cloud data pipelines for perception ML models. Scale data engine for high-fidelity labels, reduce annotation costs, integrate foundation models for automated labeling and QA, leverage software/hardware-in-the-loop testing, and support DoD field use cases and model deployment lifecycle.

Build a full-stack command-and-control platform for defense applications. Responsibilities include developing configurable frontend interfaces with 2D/3D visualizations, supporting live and simulated data, integrating with simulators and autonomous systems, and collaborating with Design to create intuitive mission-planning, monitoring, and debrief workflows. The role requires strong UI/UX judgment, spatial reasoning, and the ability to work on a rapidly iterating product team.

Develop and deploy learned manipulation policies on physical robots for industrial tasks. Responsibilities include demonstration collection, data curation, policy training and fine-tuning, real-robot evaluation, edge deployment, failure diagnosis, and performance optimization. The role covers tasks such as pick-and-place, bimanual handling, and contact-rich assembly, while improving success rate, cycle time, intervention rate, and transferability across robots.

Integrate autonomous drone systems across hardware, embedded Linux, edge software, networks, sensors, and flight operations. Lead system bring-up from bench configuration through flight testing, deploy Dockerized software, troubleshoot vehicle and payload interfaces, develop Python and C++ tooling, fabricate wiring harnesses, perform soldering and electronic diagnostics, and configure communications among flight controllers, onboard computers, radios, and ground stations.

Design, develop, and integrate real-time sensor fusion and perception algorithms across heterogeneous platforms and sensors. Deploy ML models and containerized solutions to embedded Linux devices, support DoD field tests, perform computer-/hardware-in-the-loop testing, and collaborate with tracking and autonomy teams to deliver and document robust autonomy solutions.

Build and maintain scalable HD mapping infrastructure for autonomous vehicles and robotics. Responsibilities include distributed simulation workflows, map creation and lifecycle systems, spatial query services, geospatial data tooling, map validation, troubleshooting autonomy failures, and customer collaboration. The role requires software engineering expertise across distributed systems, data pipelines, mapping, localization, and simulation.

Build and operate a self-service calibration platform for autonomous vehicle fleets. Responsibilities include onboarding vehicle types, debugging cloud and vehicle systems, orchestrating calibration workflows, creating automated data-health gates for sensor data, developing production tooling, and coordinating systemic reliability improvements across teams. The role requires strong Python and modern C++, cloud workflow orchestration, CI/CD, containerization, large-scale data pipelines, sensor and robotics knowledge, and experience with physical systems or hardware-in-the-loop.

Integrate autonomy software with vehicle platforms from architecture and interface definition through on-vehicle validation and handoff. Design compute, networking, power, sensor, and actuation systems; configure Linux and real-time platforms; develop drive-by-wire and sensor integrations; build test benches and automation; debug software-to-actuator issues; establish integration standards; mentor engineers; and support vehicle and test-track testing with approximately 10% travel.

Deploys, integrates, and operationalizes vehicle intelligence products for customers in complex environments. Combines software engineering, operating system configuration, system deployment, hardware integration, and customer engagement. Designs scalable architectures, bridges customer systems with Applied Intuition solutions, collaborates across engineering and product teams, and owns technical outcomes through project completion while adapting to changing requirements.