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Sensor Fusion Engineer, Autonomy

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

Serve Robotics aims to develop dependable and proficient sidewalk autonomy software. Our Autonomy team is looking for a highly skilled Sensor Fusion Engineer. In this role, you will be responsible for developing and maintaining our onboard sensor-to-obstacle pipeline, ensuring robust and reliable perception for our sidewalk delivery robots. You will work with a diverse set of sensor modalities—including mono and stereo cameras, LiDAR etc and dive deep into the mechanics of sensor optics, firmware, and calibration. This role demands strong production-level C++ expertise, with additional skills in CUDA, edge-device perception, machine learning, and sensor calibration considered a plus.

Responsibilities

  • Lead, design, implement, and optimize sensor fusion algorithms to reliably detect and track obstacles.

  • Develop robust pipelines that integrate data from multiple sensor modalities (cameras, LiDAR, RealSense) in real-time.

  • Develop geometric perception pipelines such as point cloud labeling, occupancy grid map generation, obstacle detection etc tailored for resource-constrained, real-time edge devices.

  • Develop ML based sensor fusion and obstacle detection pipelines. Fine-tune and deploy learning-based perception models using data-centric techniques.

  • Validate sensor fusion outputs against ground-truth data and refine models as necessary.

  • Write, maintain, and optimize production-level C++ code for real-time sensor data processing while maintaining strict latency requirements.

  • Implement parallel computing solutions using CUDA where applicable to enhance performance on edge devices.

  • Analyze and understand sensor specifications, operating principles, and firmware intricacies, working closely with systems and hardware teams.

  • Collaborate with system and hardware team, firmware developers, and ML specialists to ensure seamless integration of sensors with the overall perception system.

  • Work closely with sensor calibration teams to design strategies that ensure high precision and reliability.

Qualifications

  • 3+ years demonstrated industry experience working on sensor fusion applications for robotic or autonomous systems in a fast-paced innovative environment. 

  • Deep understanding of sensor technologies (cameras, LiDAR, RealSense) including optics, firmware, and data characteristics.

  • Experience in developing real-time applications and low-latency systems.

  • Production quality programming experience in C++ and Python.

  • Demonstrated skill building large system designs, gathering system requirements and identifying key stakeholders.

  • Strong communication and collaboration skills.

What Makes You Standout

  • 5+ years demonstrated industry experience working on sensor fusion applications for robotic or autonomous systems in a fast-paced innovative environment. 

  • Hands-on experience with CUDA for parallel processing and performance optimization.

  • Experience with state of the art ML approaches for obstacle detection and tracking.

  • Exposure to integrating ML models within sensor fusion pipelines.

Average salary estimate

$110000 / YEARLY (est.)
min
max
$90000K
$130000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Sensor Fusion Engineer, Autonomy, Serve Robotics

At Serve Robotics in Los Angeles, we're at the forefront of revolutionizing urban mobility with our incredible sidewalk robots. As a Sensor Fusion Engineer, you'll be a pivotal part of this journey, enhancing our robot's ability to interpret its environment by developing the onboard sensor-to-obstacle pipeline. You will dive into interesting challenges, working closely with a broad spectrum of sensors like cameras and LiDAR. Your expertise in C++, coupled with knowledge in machine learning and sensor calibration, will enable our robots to seamlessly navigate the complexities of city environments. Our collaboration-driven team is filled with industry veterans who are passionate about leveraging cutting-edge technology to create user-friendly and efficient robotic solutions. You'll get to lead your own projects, implement enhanced sensor fusion algorithms, and collaborate with various teams to ensure that our robots operate safely and accurately. Join us and contribute to making robotic deliveries a norm in every neighborhood, while enjoying a friendly work atmosphere that values creativity, innovation, and teamwork.

Frequently Asked Questions (FAQs) for Sensor Fusion Engineer, Autonomy Role at Serve Robotics
What responsibilities does a Sensor Fusion Engineer at Serve Robotics have?

A Sensor Fusion Engineer at Serve Robotics is tasked with leading the design and implementation of sensor fusion algorithms for our delivery robots. This includes developing pipelines that integrate data from various sensors like LiDAR and cameras, ensuring real-time processing for obstacle detection and tracking. You'll also analyze and validate sensor outputs, collaborate with hardware and firmware teams, and optimize C++ code for production-level performance while adhering to strict latency requirements.

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What qualifications do I need to become a Sensor Fusion Engineer at Serve Robotics?

To qualify for the Sensor Fusion Engineer position at Serve Robotics, candidates should have at least 3 years of industry experience in sensor fusion applications, ideally within robotic or autonomous systems. A deep understanding of sensor technologies, strong programming skills in C++ (with Python as a plus), and experience in developing real-time applications are essential. Excellent communication and collaboration skills are also crucial, as you'll work closely with diverse teams.

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What makes the Sensor Fusion Engineer role at Serve Robotics unique?

The Sensor Fusion Engineer role at Serve Robotics is special because it combines cutting-edge technology in robotics with real-world applications in urban settings. You'll have the chance to work with advanced sensor modalities, participate in the development of autonomous delivery systems, and engage in innovative problem-solving within a dynamic team of skilled professionals who are passionate about technology and user experience.

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What technologies should I be familiar with as a Sensor Fusion Engineer at Serve Robotics?

As a Sensor Fusion Engineer at Serve Robotics, familiarity with technologies such as LiDAR, RealSense cameras, and geometric perception pipelines is essential. You should also have solid production-level experience in C++ and ideally some knowledge of CUDA for parallel computing. An understanding of machine learning approaches for obstacle detection and sensor calibration will further strengthen your application.

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What is the work environment like for a Sensor Fusion Engineer at Serve Robotics?

The work environment for a Sensor Fusion Engineer at Serve Robotics is collaborative and innovative, characterized by a culture that supports diverse perspectives and skill sets. You'll be surrounded by talented professionals who are eager to think creatively about solutions to complex challenges in robotics. The team values agile work practices and a strong focus on user experience, making it a dynamic place to develop and grow your career.

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Common Interview Questions for Sensor Fusion Engineer, Autonomy
Can you describe your experience with sensor fusion in robotic systems?

In this question, aim to articulate specific projects you've worked on that required sensor fusion techniques. Discuss the types of sensors you utilized and the algorithms you developed or implemented, focusing on the impact of your work on enhancing the robot's performance.

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How do you approach the development of algorithms for real-time sensor data processing?

Your response should highlight your understanding of algorithm efficiency and optimization strategies. Discuss how you prioritize latency and computational resource management to ensure real-time processing while maintaining accuracy in sensor data interpretation.

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What challenges have you faced when working with multiple sensor modalities?

In your answer, discuss specific obstacles you've encountered, such as sensor calibration or data integration. Explain how you addressed these challenges, demonstrating your problem-solving skills and adaptability in fast-paced environments.

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How do you validate the performance of your sensor fusion algorithms?

Discuss the methods you use to validate algorithms, such as comparing outputs against ground-truth data or running controlled tests. Emphasize your commitment to accuracy and reliability in sensor fusion systems.

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What programming languages are you proficient in, particularly for sensor fusion tasks?

Mention your proficiency in C++ and Python, detailing how you've used these languages to implement sensor fusion algorithms. Highlight any specific libraries or tools you are familiar with that enhance your programming capabilities in robotics.

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Can you explain the significance of CUDA in sensor data processing?

Explain CUDA's role in parallel processing for real-time applications. Discuss how you've leveraged CUDA to improve performance and reduce processing times in your past projects, focusing on specific examples.

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How do you ensure the seamless integration of sensors with a perception system?

Your answer should showcase your collaboration skills. Discuss how you work with hardware, firmware, and machine learning teams to achieve successful sensor integration and the importance of communication and teamwork in this process.

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Describe a project where you optimized sensor fusion algorithms for an edge device.

Talk about your hands-on experience with a specific project. Discuss the optimizations you implemented, the technologies used, and the results achieved, emphasizing how you balanced performance and resource constraints.

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What machine learning techniques have you implemented for sensor fusion?

Describe any ML approaches you've applied in sensor fusion contexts. Discuss your experience with model training, validation, and deployment, emphasizing the effectiveness of your solutions in improving perception.

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How do you stay current with advances in sensor technologies and fusion techniques?

Highlight your dedication to continuous learning. Mention any conferences, publications, or online courses you follow to keep your knowledge updated, demonstrating your commitment to staying at the cutting edge of sensor fusion engineering.

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Why deliver a 2-pound burrito in a 2-ton car? Serve is the future of sustainable, self-driving delivery. Our zero-emissions rovers are designed to serve people in public spaces, starting with food delivery. We partner with platforms and merchants ...

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Full-time, on-site
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March 18, 2025

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