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Robotics Perception Jobs in Texas (NOW HIRING)

Saronic Technologies

Perception Hardware Engineer

Austin, TX · On-site

$122K - $161K/yr

Job Overview We are seeking a Perception Hardware Engineer to join a team that will integrate and ... Bachelor's degree or greater in Mechanical Engineering, Robotics, Electrical Engineering, or a ...

ARM

Head of Robotics Systems

Austin, TX · Hybrid

$308K - $417K/yr

Define system architectures that integrate perception, reasoning, planning, and control * Lead end-to-end system bring-up, integration, and validation across robotic platforms * Drive execution of ...

ARM

Head of Robotics Systems

Austin, TX · On-site

$308K - $417K/yr

Define system architectures that integrate perception, reasoning, planning, and control * Lead end-to-end system bring-up, integration, and validation across robotic platforms * Drive execution of ...

Neuralink

Software Engineer Intern, Robotics

Austin, TX · On-site

$35/hr

The Robot Software Team builds software that enables scalable neurosurgery that allows safe implantation of the N1 device, ranging from core control, sensors and perception, autonomy, surgery ...

ICON

Senior Robotics Software Engineer I

Austin, TX · On-site

$121K - $160K/yr

Hands-on experience with robotic platforms, sensors, actuators, localization, perception, and control systems. * Practical experience designing and optimizing sensor fusion and state estimation ...

Neuralink

Software Engineer Intern, Robotics

Austin, TX · On-site

$35/hr

The Robot Software Team builds software that enables scalable neurosurgery that allows safe implantation of the N1 device, ranging from core control, sensors and perception, autonomy, surgery ...

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Robotics Perception information

What are some common challenges faced by professionals in Robotics Perception roles when integrating perception systems with real-world robotics applications?

A key challenge in Robotics Perception is ensuring that perception algorithms—such as object detection, mapping, and localization—operate reliably in dynamic, unstructured environments. Professionals often need to address sensor noise, variable lighting conditions, and occlusions that can impact data quality. Integrating perception systems with robotic hardware requires close collaboration with mechanical, software, and controls engineers to ensure real-time performance and robustness. Adapting solutions to different platforms and continuously validating them in field tests is also an essential, ongoing responsibility.

What is robotics perception?

Robotics perception refers to the ability of robots to interpret and understand their environment using sensors such as cameras, LIDAR, and radar. This field combines elements of computer vision, machine learning, and sensor fusion to help robots identify objects, navigate spaces, and interact with the world safely and effectively. Robotics perception is crucial for autonomous systems like self-driving cars, drones, and industrial robots, enabling them to make decisions based on real-time data from their surroundings.

What is the difference between Robotics Perception vs Robotics Software Engineer?

AspectRobotics PerceptionRobotics Software Engineer
Required CredentialsBachelor's or Master's in Robotics, Computer Science, or related fields; experience with perception algorithmsBachelor's or Master's in Computer Science, Software Engineering, or related; programming skills in C++, Python
Work EnvironmentResearch labs, R&D departments, industry settings focused on sensor data processingDevelopment teams, industrial or research settings, focusing on software development for robots
Industry UsageUsed in autonomous vehicles, drones, and robotic systems for environment understandingDevelops the software that enables robotic functionalities, including perception modules

Robotics Perception specialists focus on developing algorithms that interpret sensor data to understand the environment, while Robotics Software Engineers build the overall software systems that incorporate perception modules. Both roles often collaborate but differ in their core focus and skill sets.

What are the key skills and qualifications needed to thrive as a Robotics Perception Engineer, and why are they important?

To thrive as a Robotics Perception Engineer, you need a solid background in computer vision, machine learning, and robotics, typically supported by a degree in computer science, engineering, or a related field. Experience with tools like ROS (Robot Operating System), OpenCV, and programming languages such as Python or C++ is essential, along with familiarity with sensor technologies and perception algorithms. Strong problem-solving skills, teamwork, and clear communication are crucial soft skills for addressing complex challenges and collaborating effectively. These abilities ensure robust perception systems, enabling robots to interpret and interact safely and efficiently with their environments.
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Robotics Perception jobs near you
Sr. Software Engineer - Simulation / Support

Sr. Software Engineer - Simulation / Support

Diligent Robotics

Austin, TX • On-site

Other

Posted 14 days ago

Job description

What we're doing isn't easy, but nothing worth doing ever is. 

We envision a future powered by robots that work seamlessly with human teams. At Diligent Robotics, we build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic, human-filled environments.

Diligent is one of the only companies in the world operating a production fleet of mobile manipulation robots in real environments. Every day, our robots work alongside hospital staff, generating the real-world data needed to advance the next generation of Physical AI. If you're excited about solving the hardest problems in robotics, where simulation meets real-world deployment, this is the job for you.

As a Senior Software Engineer - Simulation / Support, you will accelerate the effectiveness of our engineering organization. This hybrid role spans developer tooling, software support and triage, and simulation infrastructure. You will help engineers build better software, faster, while strengthening the reliability and debuggability of our robotics stack in production.

You will develop state-of-the-art infrastructure to test and validate Physical AI models, and help bridge the gap between simulation and reality by improving synthetic data and scenario generation with real-world data from our growing fleet of operational robots.

Responsibilities
  • Design and build tools that improve productivity and debugging across the robotics software stack
  • Develop and maintain simulation infrastructure used for testing autonomy, navigation, perception, manipulation and system level behaviors
  • Partner with autonomy, perception, platform, and infrastructure teams to integrate simulation into CI pipelines and validation workflows
  • Create reproducible test harnesses and simulation scenarios that mirror real world operational edge cases found in our customer environments
  • Support release readiness by strengthening automated validation, regression testing, and scenario based simulation coverage
  • Contribute to architecture decisions that improve modularity, testability, and long term maintainability of the codebase
  • Evaluate and integrate third party simulation frameworks or build custom simulation tooling as needed
  • Mentor engineers on best practices in testing, debugging, observability, and system design
Basic Qualifications
  • Undergraduate or graduate degree in Robotics, Computer Science, Electrical Engineering, or related field.
  • 5+ years of professional software engineering experience, ideally in robotics, autonomous vehicles, or other complex cyber physical systems
  • Strong proficiency in C++ and/or Python
  • Experience with robotic middleware such as ROS or similar distributed systems frameworks
  • Experience developing or extending simulation environments, such as Gazebo, Isaac Sim, Mujoco, or custom in house engines
  • Experience debugging distributed systems and working with real world hardware
  • Strong understanding of software architecture, systems design, and scalable tooling
  • Familiarity with CI/CD systems and automated testing frameworks
  • Comfort working across the stack, from low level systems to higher level autonomy behaviors
  • Excellent cross functional communication skills and a bias toward pragmatic solution

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