Senior Machine Learning Engineer, Perception

PlusAI is building perception capabilities for autonomous driving and 3D scene understanding, with an emphasis on Bird’s Eye View (BEV) modeling that can combine multiple sensor sources. In this onsite role in Santa Clara, CA, you will design and deliver scalable perception algorithms, particularly for LiDAR-based fusion, while working closely with research, data, and deployment teams.

What you’ll do

• Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs.
• Benchmark perception models using large-scale datasets with quantitative metrics to validate performance.
• Collaborate cross-functionally with research, data, and deployment engineers to refine models and support real-world applications.
• Focus on performance, robustness, and scalability to support production deployment needs.
• Ensure your work follows the company’s Quality Management System (QMS) requirements and contribute to continuous improvement.
• Support team compliance with QMS by monitoring quality and driving process improvements.

What you’ll bring

• Ph.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field.
• Ph.D. new grad or Masters + 3 years of industry experience.
• Proficiency in Python and experience building deep learning pipelines.
• Strong expertise with PyTorch, TensorFlow, or JAX.
• Proven experience in LiDAR-based 3D perception and BEV representation models.
• Deep understanding of multimodal sensor fusion architectures and techniques.
• Familiarity with camera, LiDAR, and radar modalities, including synchronization, calibration, and integration in perception pipelines.
• A solid foundation in computer vision, deep learning, and 3D geometry.

Technologies

• Python
• PyTorch
• TensorFlow
• JAX

Compensation and benefits

• $150,000 - $200,000 per year (USD).
• 401(k) plan included as part of a highly competitive salary and benefits package.
• Catered free lunch, unlimited snacks and beverages.
• Opportunities to work, learn, and grow in a future-oriented, innovative, and dynamic field.
• Wide range of opportunities for personal and professional development.

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.