Aeva’s mission is to bring the next wave of perception to a broad range of applications from automated driving to industrial robotics, consumer electronics, consumer health, security, and beyond. Aeva is transforming autonomy with its groundbreaking sensing and perception technology that integrates all key LiDAR components onto a silicon photonics chip in a compact module. Aeva 4D LiDAR sensors uniquely detect instant velocity in addition to 3D position, allowing autonomous devices like vehicles and robots to make more intelligent and safe decisions.

Role Overview:

We are seeking a highly skilled and motivated Machine Learning Engineer with a focus on Perception technologies such as object detection and semantic segmentation. The ideal candidate will have a deep understanding of ML/DL technologies and frameworks, excellent Python and C++ skills, and hands-on experience with PyTorch. You will be instrumental in developing and deploying state of-the-art perception systems on embedded platforms.

What you'll do:

Develop and implement state-of-the-art machine learning models for object detection and semantic segmentation tasks, using PyTorch.
Prototype new algorithms, design and carry out experiments to demonstrate their effectiveness.
Optimize algorithms for real-time execution on embedded platforms and ensure robust and efficient deployment using TensorRT and CUDA.
Collaborate with the broader team to define product requirements, system design, and algorithm development.
Stay up-to-date with the latest advances and trends in machine learning and artificial intelligence.
Debug and solve complex technical issues related to ML/DL models and deployment

What you have:

Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or a related field.
Proven experience as an ML Engineer or similar role, with a focus on object detection and semantic segmentation.
Proficient in Python and PyTorch for designing, developing, and testing machine learning models.
Experience with deploying ML/DL models on embedded platforms using TensorRT and CUDA.
Familiarity with state-of-the-art machine learning algorithms and perception technologies.
Excellent problem-solving abilities and attention to detail.
Strong communication and team-working skills.

Nice to have:

Experience with writing inference code in C++ for real-time applications and performance optimization.
Exposure to automotive development processes.
Prior knowledge of embedded device software development process and lifecycle