Zensors · 17 hours ago
AI Infrastructure Engineer
San Francisco, CA
Full-time
Onsite
Mid, Senior LevelZensors is a spatial intelligence platform that provides real-time insights to help organizations make smarter operational decisions. The AI Infrastructure Engineer will develop technologies to accelerate the training and inference of computer vision models, focusing on optimizing the AI workflow lifecycle and enhancing video data processing capabilities.
Computer Software
Responsibilities
Optimizing Core ML Pipelines: Identifying key bottlenecks in our current video analytics pipeline and performing in-depth analysis to ensure the best possible performance on current server and edge compute architectures
Cross-Stack Collaboration: Collaborating closely with AI research and platform engineering teams to optimize core parallel algorithms and influence the design of our next-generation inference infrastructure
Model Acceleration: Applying advanced model optimization techniques—such as quantization (Int8/FP16), pruning, and layer fusion—to our Vision Transformers (ViTs) and CNNs to maximize throughput and minimize latency
Building Efficient Operators: Working across the entire ML framework/compiler stack (e.g., PyTorch, CUDA, TensorRT, and NVIDIA DeepStream) to write custom optimized ML operator libraries
Resource Efficiency: Reducing the compute cost per video stream to enable massive scalability of our SaaS product
Data Management: Building, improving, maintaining, and operating systems to facilitate the collection, labeling, and use of visual data for ML training
Qualification
Required
BS/MS or Ph.D. in Computer Science, Electrical Engineering, or a related discipline
Strong programming skills in C/C++ and Python
Experience with model optimization, quantization, and efficient deep learning techniques (e.g., knowledge distillation, pruning)
Deep understanding of GPU hardware performance, including execution models, thread hierarchy, memory/cache management, and the cost/performance trade-offs of video processing
Experience with profiling and benchmarking tools (e.g., Nsight Systems, Nsight Compute) to validate performance on complex architectures
Experience identifying and resolving compute and data flow bottlenecks, particularly in high-bandwidth video processing pipelines
Strong communication skills and the ability to work cross-functionally between research and infrastructure teams
Preferred
Familiarity with database systems (e.g., SQL, Neo4j)
Work in Computer Vision, Deep Learning, and Vision Transformers
Experience with video processing frameworks such as NVIDIA DeepStream, DALI, or FFmpeg
Familiarity with ML compilers (e.g., TVM, MLIR) or inference engines like TensorRT or ONNX Runtime
Knowledge of distributed training systems or cloud-scale inference serving (e.g., Triton Inference Server)
Company
Zensors
Physical AI for the understanding the real world
Founded in 2019
51-200 employees
H1B Sponsorship
Zensors has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2024 (2)
2022 (1)
2021 (1)
2020 (1)
Funding
Current Stage
Growth StageTotal Funding
unknownKey Investors
Y Combinator
2022-09-09Seed
2021-08-31Pre Seed
2019-06-01Non Equity Assistance
Leadership Team
Chris Harrison
Technology
Company data provided by crunchbase