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

To thrive as a Perception Algorithm Engineer, you need a strong background in computer vision, machine learning, and programming (typically C++ or Python), often supported by a degree in computer science, robotics, or a related field. Familiarity with tools like TensorFlow, PyTorch, OpenCV, and ROS, as well as experience with sensor data (e.g., LiDAR, cameras), is crucial. Strong analytical thinking, problem-solving abilities, and effective teamwork are standout soft skills for this role. These skills are vital to develop robust perception systems that enable autonomous vehicles and robots to interpret and interact safely with complex real-world environments.

What are some common challenges faced by Perception Algorithm Engineers when integrating their solutions into autonomous systems?

Perception Algorithm Engineers often encounter challenges when ensuring their algorithms perform reliably in diverse real-world environments, such as varying lighting, weather conditions, and sensor noise. Integrating algorithms with hardware requires close collaboration with robotics and systems engineering teams to optimize performance and latency. Additionally, balancing accuracy with computational efficiency is crucial, as perception modules must run in real time on embedded systems. Addressing these challenges involves rigorous testing, continuous model improvement, and effective cross-functional communication.

What is a Perception Algorithm Engineer?

A Perception Algorithm Engineer is a professional who develops algorithms that enable machines—such as autonomous vehicles or robots—to interpret and understand sensory data from their environment. This typically involves processing data from cameras, lidar, radar, and other sensors to identify objects, track movement, and understand surroundings. Perception Algorithm Engineers work with computer vision, sensor fusion, and machine learning techniques to create reliable and efficient perception systems. Their work is crucial in making machines aware of their surroundings and enabling them to respond appropriately. They often collaborate with hardware, software, and robotics teams to integrate their algorithms into real-world applications.
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Infographic showing various Perception Algorithm Engineer job openings in Indiana as of May 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Temporary. Highlights an 100% Physical job distribution.
Senior Radar Systems Lead - Robotics & Drones

Senior Radar Systems Lead - Robotics & Drones

Aptiv PLC

Westfield, IN • On-site

Full-time

Posted 24 days ago

Job description

Senior Radar Systems Lead - Robotics & Drones
We are Aptiv - a global technology company with 200,000 specialists in 48 countries. We develop innovative software and build the hardware to bring autonomous driving cars, advanced driver-assistance systems, connected vehicles and smart cities to life in a way that only we can. We work in partnership with almost all car manufacturers. Our sensors, systems and software can already be found in almost all passenger cars today.
We are building a new Robotics business at Aptiv, focused on Autonomous Mobile Robots (AMRs) and Drones for warehouse, industrial, and adjacent markets. As a Sr Radar Systems Lead, you will work closely with product management, hardware/SoC teams, and engineering partners to turn PoCs into scalable, reusable architectures that can be deployed across multiple customers and robot form factors.
We are seeking a Senior Radar Systems Engineer with deep expertise in radar system design, signal processing, and end-to-end sensing architecture for advanced AMR and drone platforms. This role emphasizes ownership of radar-centric systems-from sensor characteristics and waveform design through signal processing pipelines and perception integration-while leveraging modern software tooling and cloud-based infrastructure to enable scalable development, validation, and deployment.
You will lead the design and technical direction of radar-enabled sensing systems, bridging theory, algorithm development, and real-world deployment across autonomous platforms.
Key Responsibilities:
Radar Systems Engineering & Signal Processing
  • Own the end-to-end radar sensing architecture, including waveform selection, signal chain design, calibration, and performance characterization.
  • Design and develop radar signal processing pipelines focused on raw data ingestion, range/Doppler processing, beamforming, detection, tracking, and classification.
  • Define system-level performance requirements (range, resolution, latency, power, interference robustness) and ensure alignment across hardware and software.
  • Develop and maintain MATLAB-based radar analysis and modeling tools for algorithm development, system validation, and performance evaluation.
  • Analyze real-world radar data to validate models, tune algorithms, and improve robustness across diverse environments.
  • Collaborate with perception teams to integrate radar outputs into multi-sensor fusion frameworks (radar & camera).
  • Conduct anechoic chamber testing to verify radar concepts and validate algorithm performance.
  • Participate in robotics and drone testing to validate radar sensor performance in real-world environments

System Architecture & Integration
  • Support the system architecture of radar-enabled AMR and drone platforms, spanning radar sensors, & onboard compute.
  • Define interfaces and data flows between radar subsystems, perception stacks, autonomy modules, and external services.
  • Partition processing across sensor-level, & edge, optimizing for latency, bandwidth, and scalability.
  • Support integration with ROS 2, Linux-based systems, and real-time middleware, ensuring robust communication across distributed components.
  • Work closely with hardware teams to ensure proper sensor integration, synchronization, and calibration within the broader system.

Algorithm Development & Deployment
  • Develop, prototype, and validate radar signal processing algorithms in MATLAB, and guide their transition into production environments.
  • Ensure algorithms are robust to real-world challenges such as noise, multipath, interference, and environmental variability.
  • Support development of containerized data processing pipelines for large-scale radar data analysis and validation.
  • Define and maintain data standards, labeling approaches, and evaluation metrics for radar perception systems.

Technical Leadership
  • Drive the development of next-gen radar systems from inception to realization, including requirements analysis, algorithm development, and system concept architectures
  • Lead system-level trade studies across radar modalities, processing architectures, and compute platforms.
  • Provide technical direction across radar system design, signal processing, and perception integration.
  • Mentor engineers on best practices in radar system modeling, validation, and deployment workflows.
  • Collaborate with hardware, embedded, and compute teams to map workloads across CPU, GPU, DSP, and specialized accelerators.

Customer & Partner Engagement
  • Translate customer and partner requirements into radar system specifications and sensing architectures.
  • Support proofs of concept, demonstrations, and field deployments involving radar-enabled perception.
  • Contribute to long-term technology roadmaps spanning radar hardware, signal processing, and autonomy integration.

Basic Qualifications:
  • Bachelor's or Master's degree in Electrical Engineering, Robotics, Physics, Computer Engineering, or equivalent experience.
  • 5+ years of experience in radar systems engineering, sensing systems, or autonomous platforms.
  • Strong background in radar signal processing fundamentals (FMCW, pulse radar, Doppler processing, detection, tracking).
  • Proven experience with real-world radar systems, including data collection, calibration, and performance evaluation.
  • Proficiency in MATLAB for modeling, simulation, and algorithm development.
  • Understanding of system architecture, embedded systems, and real-time processing constraints.
  • Strong analytical, debugging, and system validation skills.
  • Familiarity with anechoic chamber testing and vehicle-level testing methodologies.
  • Excellent communication skills for conveying complex technical concepts.

Preferred Qualifications:
  • Deep expertise with FMCW radar systems, including waveform design and MIMO/beamforming techniques.
  • Experience with multi-sensor fusion (radar + vision).
  • Familiarity with antenna systems, RF front-end design, or electromagnetic considerations.
  • Experience transitioning research algorithms into production systems.
  • Experience with cloud-based data pipelines for large-scale sensor data processing and analytics.
  • Familiarity with simulation environments and data replay tools for sensor validation.
  • Experience with heterogeneous compute platforms (GPU, DSP, FPGA, or NPU) for signal processing workloads.
  • Background in autonomous systems (AMR, drones, automotive, or robotics platforms).
  • Experience working with Linux and robotics middleware (ROS/ROS 2 or similar).
  • Experience working in fast-paced, ambiguous environments.

Traits we seek:
  • Curiosity-driven problem solvers who investigate deeply and think systemically.
  • Confident leaders who empower teams, set direction, and earn trust.
  • Hands-on learners with an experimental, builder mindset.
  • Resilient thinkers who see challenges as opportunities to learn and improve.

Privacy Notice - Active Candidates: https://www.aptiv.com/privacy-notice-active-candidates
Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.

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