Senior Machine Learning Engineer, Perception
Santa Clara, CA
- Pay
USD 150,000–200,000/year — pay source
Salary 150,000 – 200,000 USD per year Your opportunities joining PlusAI
Read the full posting- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign, implement, and optimize BEV-based perception models fusing camera, LiDAR, and radar
Benchmark perception models on large-scale datasets using quantitative metrics
Work with research, data, and deployment engineers to refine models for real-world use
Keep models robust, performant, and scalable for production systems
From the employer’s posting
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.
What you’ll bring
All qualificationsCore experience
- Master's or PhD in AI, computer science, EE, robotics, or related field
- PhD new grad, or Master's plus 3 years industry experience
- Proficiency in Python and building deep learning pipelines
- Strong expertise in PyTorch, TensorFlow, or JAX
- Proven experience with LiDAR-based 3D perception and BEV models
Preferred experience
- Hands-on experience developing deep learning models in real-world or production environments.
- Experience with distributed training, high-performance computing, or GPU acceleration.
Qualification wording
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
Hands-on experience developing deep learning models in real-world or production environments.
Experience with distributed training, high-performance computing, or GPU acceleration.
Education & alternatives
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
- 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.
Tools in this posting
- Python
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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.
- 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 17, 2026 · 13 days ago
- Recorded sightings
- 17
- Last seen by us
- Oct 31, 2026
- Employer says posted
- Aug 4, 2026
- Reposted
- once since Aug 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
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.
Salary
150,000 – 200,000 USD per year
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 150,000 – 200,000 USD per year Your opportunities joining PlusAI
- Location & working pattern
Santa Clara, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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