Perception Engineer

Perception Engineer

Newport +1 Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and deploy real-time perception systems for robotic manipulation.
  • Company: Join Kinisi Robotics, a leader in innovative robotic solutions.
  • Benefits: Enjoy competitive salary, equity, flexible hours, and health coverage.
  • Why this job: Be at the forefront of robotics, blending research with real-world applications.
  • Qualifications: PhD or outstanding Master's in relevant fields; 3+ years experience required.
  • Other info: Work in a state-of-the-art lab with collaborative teams.

The predicted salary is between 36000 - 60000 £ per year.

We’re building the next generation of robot manipulation systems for unstructured, real-world environments. As a Perception Engineer, you will design, prototype, and deploy high-performance perception pipelines that enable our robots to see, understand, and dexterously interact with the world in real time. You’ll sit at the intersection of academia and product, translating state-of-the-art research into production-ready software running on ROS 2 based platforms.

What You’ll Do

  • Own the real-time perception stack for robotic manipulation tasks, from sensor acquisition through to fused 3-D scene understanding and grasp/placement proposals.
  • Research, prototype, and benchmark novel algorithms in 2-D/3-D vision, multi-modal fusion, and dense correspondence that push manipulation speed and reliability.
  • Implement, optimize, and profile deep-learning models in PyTorch and C++ (CUDA) to meet strict latency budgets on embedded GPUs/accelerators.
  • Integrate perception modules in ROS 2, ensuring clean interfaces, deterministic scheduling, and robust failure handling.
  • Conduct rigorous real-world and simulated experiments, and communicate results through clear technical reports and publications (internal and external).
  • Collaborate cross-functionally with controls, planning, and hardware teams to close perception–action loops and ship production-quality releases.

Minimum Qualifications

  • PhD (or outstanding Master’s + equivalent publications) in Robotics, Computer Vision, Machine Learning, or a closely related field.
  • 3+ years hands-on experience building real-time perception systems for robot manipulation or autonomous platforms.
  • Advanced proficiency in Python and modern C++17/20; proven track record writing clean, testable, high-performance code.
  • Deep expertise with PyTorch (training & inference) and GPU programming (CUDA, TensorRT, or similar).
  • Production experience with ROS 2 (rclcpp/rclpy, lifecycle nodes, DDS tuning, real-time QoS).
  • Strong publication record in top-tier venues (e.g., RSS, ICRA, CoRL, CVPR, RAL).

Preferred Qualifications

  • Track record shipping perception on manipulation platforms (e.g., mobile manipulators, bin-picking arms, industrial cobots).
  • Familiarity with multi-sensor calibration, tactile or force perception, depth cameras (D-ToF, active stereo), and point-cloud processing (PCL, Open3D).
  • Experience deploying on-device inference for NVIDIA Jetson/Orin, Intel ARC, or similar edge accelerators.
  • Contributions to open-source robotics or vision libraries.
  • Comfortable working in an agile, research-driven environment with fast iteration cycles.

What We Offer

  • Competitive salary, equity, and performance bonus.
  • Comprehensive health, dental, and vision coverage.
  • Annual conference budget & dedicated research time.
  • Flexible hours and hybrid/remote-friendly culture.
  • State-of-the-art lab space with collaborative, cross-disciplinary teams.

Locations

Newport Wales

Perception Engineer employer: Kinisi Robotics

At Kinisi Robotics, we pride ourselves on being an exceptional employer, particularly for those passionate about advancing robotics in the vibrant city of Bristol. Our collaborative work culture fosters innovation and creativity, offering employees ample opportunities for professional growth through dedicated research time and an annual conference budget. With competitive salaries, comprehensive health benefits, and a hybrid work model, we ensure that our team members thrive both personally and professionally while contributing to groundbreaking projects in real-time manipulation robotics.
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Contact Detail:

Kinisi Robotics Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Perception Engineer

✨Tip Number 1

Familiarise yourself with the latest advancements in perception systems and robotics. Follow relevant research papers and publications, especially those from top-tier venues like RSS and CVPR, to stay updated on cutting-edge techniques that you can discuss during interviews.

✨Tip Number 2

Engage with the robotics community by attending conferences or workshops. Networking with professionals in the field can provide insights into industry trends and may even lead to referrals for job openings at companies like us.

✨Tip Number 3

Showcase your hands-on experience with real-time perception systems through personal projects or contributions to open-source initiatives. This practical experience will not only enhance your skills but also demonstrate your passion and commitment to potential employers.

✨Tip Number 4

Prepare to discuss your experience with ROS 2 and deep learning frameworks like PyTorch in detail. Be ready to explain how you've implemented and optimised algorithms in past projects, as this technical knowledge is crucial for the role of a Perception Engineer.

We think you need these skills to ace Perception Engineer

Real-Time Perception Systems
2-D/3-D Vision Algorithms
Multi-Modal Fusion
Dense Correspondence Techniques
Deep Learning with PyTorch
C++ Programming (C++17/20)
GPU Programming (CUDA, TensorRT)
ROS 2 Integration (rclcpp/rclpy)
Sensor Acquisition and Processing
Robust Failure Handling
Technical Report Writing
Cross-Functional Collaboration
Publication in Top-Tier Venues
On-Device Inference Deployment
Multi-Sensor Calibration
Point-Cloud Processing (PCL, Open3D)
Agile Development Methodologies

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in robotics, computer vision, and machine learning. Emphasise your hands-on experience with real-time perception systems and any specific projects that align with the role.

Craft a Strong Cover Letter: In your cover letter, express your passion for robotics and how your background makes you a perfect fit for the Perception Engineer position. Mention specific skills like proficiency in Python, C++, and experience with ROS 2 that are crucial for the role.

Showcase Your Publications: If you have a strong publication record, include a section in your application that lists your most relevant papers. Highlight those published in top-tier venues to demonstrate your expertise and contributions to the field.

Prepare for Technical Questions: Anticipate technical questions related to perception algorithms, deep learning models, and ROS 2 integration. Be ready to discuss your previous projects and how they relate to the responsibilities of the Perception Engineer role.

How to prepare for a job interview at Kinisi Robotics

✨Showcase Your Technical Skills

Be prepared to discuss your experience with real-time perception systems, particularly in robotics. Highlight specific projects where you've implemented algorithms in 2-D/3-D vision or worked with ROS 2, as this will demonstrate your hands-on expertise.

✨Prepare for Problem-Solving Questions

Expect technical questions that assess your ability to tackle challenges in perception engineering. Practice explaining your thought process when developing solutions, especially regarding sensor acquisition and scene understanding.

✨Demonstrate Your Research Acumen

Since the role involves translating research into practical applications, be ready to discuss your publications and how they relate to the position. This shows your ability to bridge the gap between academia and industry.

✨Emphasise Collaboration Skills

The job requires working closely with cross-functional teams. Share examples of past collaborations, focusing on how you effectively communicated and integrated your work with others, particularly in agile environments.

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