Design and develop Bird’s Eye View fusion models for autonomous driving using multimodal sensor inputs like LiDAR, focusing on performance, robustness, and scalability.
We are seeking a highly skilled Machine Learning Engineer with deep expertise in developing Bird’s Eye View (BEV) fusion models using multimodal sensor inputs, particularly LiDAR. You will play a central role in designing scalable perception algorithms that integrate data from camera, LiDAR, and radar sensors to support autonomous driving and 3D scene understanding.
Responsibilities:
- Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs.
- Benchmark perception models using large-scale datasets and well-defined quantitative metrics.
- Collaborate cross-functionally with research, data, and deployment engineers to refine models and support real-world applications.
- Maintain a strong focus on performance, robustness, and scalability for deployment in production systems.
- Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
- Ensure team compliance with QMS, monitor quality, and drive process improvements.
Required Skills:
- Ph.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field.
- Ph.D. new grad or Masters + 3 years industry experience
- Proficiency in Python and experience building deep learning pipelines.
- Strong expertise in PyTorch, TensorFlow, or JAX.
- Proven experience with LiDAR-based 3D perception and BEV representation models
- Deep understanding of multimodal sensor fusion architectures and techniques.
- Familiarity with camera, LiDAR, and radar modalities and their synchronization, calibration, and integration in perception pipelines.
- Solid foundation in computer vision, deep learning, and 3D geometry.
Preferred Skills:
- Industry or academic experience in autonomous vehicle perception, robotics, or related areas.
- Hands-on experience developing deep learning models in real-world or production environments.
- Experience with distributed training, high-performance computing, or GPU acceleration.
Plus Santa Clara, California, USA Office
3315 Scott Blvd, Santa Clara, California, United States, 95054
Similar Jobs
Hardware • Energy • Defense • Automation
The Senior Machine Learning Engineer will lead the perception stack, focusing on detection, tracking, classification, and sensor fusion for targeting systems, with responsibilities including model development and real-time optimization on embedded devices.
Top Skills:
C++OnnxPythonTensorrt
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
As a Senior Machine Learning Engineer for the Localization team, you'll improve ML systems for pose estimation, integrate computer vision models, and maintain coding best practices. You'll also collaborate closely on model validation and contribute technically to team architecture.
Top Skills:
C++NumpyPythonPyTorch
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
As a Senior Machine Learning Engineer, you'll design algorithms for 2D/3D perception and mapping, lead cross-functional projects, and contribute to HD mapping pipelines.
Top Skills:
C++Python
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


