Ph.D – Autonomous Driving Specialist

Required Qualifications

Mandatory: Ph.D Completed, Active in research program.

Tecnocad is a leading engineering and design company based in Turin, Italy, with a global footprint of 500+ professionals, 7 offices across 4 continents, and over 100 projects delivered annually. Its Autonomous Vehicle (AV) division specializes in deploying turnkey autonomous driving solutions in semi-closed environments such as industrial parks, airports, and campuses, leveraging Autoware Universe and Nav2.

Tecnocad AV develops an integrated hardware and software stack for autonomous systems and holds a strong position in the national market. The team has extensive experience in vehicle-level system development, teleoperation and system integration, simulation and lightweight deployment, supported by an international R&D network.

The company is advancing its capabilities in teleoperation, data management, and scalable software architectures that integrate perception, planning, and remote control. By developing robust teleoperation systems, curated large-scale datasets, and modular high-performance software pipelines, Tecnocad aims to reduce development cycles, enhance safety, and enable scalable autonomous deployments. A proof-of-concept teleoperation platform is already available, with validation planned in simulation and controlled environments within six months.

Responsibilities

• Autonomous driving architectures, including perception, planning, and control.
• Teleoperation systems design, including real-time remote control and safety protocols.
• Data curation, annotation, and management for machine learning applications.
• Software development best practices, including modular and scalable architectures.
• Simulation platforms for autonomous driving (e.g., CARLA, LGSVL, AWSIM).
• Contribute to publications in peer-reviewed journals and international conferences.

Software Knowledge

• Programming languages: Python, C++, ROS/ROS2, and MATLAB.
• Machine learning frameworks.
• Cloud computing and data pipelines.

Relevant Experience

• Leading research or industrial projects in autonomous driving or robotics.
• Managing large-scale datasets for training, validation, or benchmarking.
• Bridging research outputs to deployed software in real-world or simulated environments.
• Publications or patents in autonomous mobility, teleoperation, or related fields.

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