AI/ML Workloads Engineer
San Jose, CA · On-site
Experience training, tuning and deploying ML models for CV (ResNet,..), NLP (BERT, GPT), and/or Recommendation Systems (DLRM) * Experience deploying ML workloads on distributed systems * Self ...
AI/ML Workloads Engineer
San Jose, CA · On-site
Experience training, tuning and deploying ML models for CV (ResNet,..), NLP (BERT, GPT), and/or Recommendation Systems (DLRM) * Experience deploying ML workloads on distributed systems * Self ...
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet ...
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet ...
Senior Computer Vision Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Experience with ResNet, MobileNet, and DeepStream * Experience with multi-camera object tracking, depth, and pose estimation * Experience deploying models with GCP Services Vertex AI and Vision OCR
Senior Computer Vision Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Experience with ResNet, MobileNet, and DeepStream * Experience with multi-camera object tracking, depth, and pose estimation * Experience deploying models with GCP Services Vertex AI and Vision OCR
Machine Learning Engineer
Los Angeles, CA · On-site
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet ...
Machine Learning Engineer
Los Angeles, CA · On-site
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet ...
Senior Machine Learning Engineer
Vista, CA · On-site
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Senior Machine Learning Engineer
Vista, CA · On-site
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Senior Machine Learning Engineer
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Senior Machine Learning Engineer
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Senior Machine Learning Engineer
Vista, CA · On-site
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Senior Machine Learning Engineer
Vista, CA · On-site
$107K - $195K/yr
Familiarity with CNN-based machine learning architectures, e.g., ResNet, Yolo, U-Net * Experience working with images from medical, security, or NDT devices * Experience defining data science ...
Resnet information
What is a ResNet job?
A ResNet job typically involves working with deep learning models based on Residual Networks (ResNet), which are widely used for image recognition and computer vision tasks. Professionals in this role may design, train, and optimize ResNet architectures for applications such as medical imaging, autonomous vehicles, or facial recognition. The job often requires expertise in machine learning frameworks like TensorFlow or PyTorch, as well as proficiency in Python and GPU acceleration.
What are the key skills and qualifications needed to thrive in the Resnet position, and why are they important?
To thrive as a ResNet technician, you need a strong understanding of computer networking, troubleshooting, and customer service, often supported by relevant IT certifications or coursework. Familiarity with network management tools, wireless access point configuration, and ticketing systems is typically required. Excellent problem-solving skills, patience, and the ability to communicate technical information clearly are valuable soft skills in this role. These abilities ensure reliable network support for residents, minimize downtime, and foster a positive user experience in residential environments.
What are the typical daily responsibilities of a ResNet technician?
As a ResNet technician, your daily responsibilities usually include responding to service requests from residents, diagnosing and resolving network connectivity issues, and maintaining residential network equipment. You may also perform scheduled maintenance on wireless access points, educate users about proper network practices, and document your troubleshooting efforts in ticketing systems. You can expect to collaborate closely with your IT team, interact directly with residents, and occasionally assist with larger network upgrades or installations. This hands-on role is ideal for those who enjoy problem-solving and making a direct impact on user satisfaction.
What are popular job titles related to Resnet jobs in California? For Resnet jobs in California, the most frequently searched job titles are:
What job categories do people searching Resnet jobs in California look for? The top searched job categories for Resnet jobs in California are:
Job description
The Role: Senior/Staff/Principal Research/SW Engineer (ML Workloads)
The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the Software team, you will be responsible for the development, enhancement, and maintenance of the development and testing infrastructure for development of next-generation AI hardware. This includes the software development repo, and the testing infrastructure for the Compiler, Kernels, and will utilize simulators, FPGAs, Emulation and the chip as test platforms. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler and ML experts to build out the testing infrastructure working closely with other software and hardware experts in the company.
Qualifications
Minimum:
- Computer Science, Engineering, Math, Physics or related degree
- MS or PhD in Computer Science, Electrical Engineering, or related fields
- Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals
- Strong theoretical understanding of machine learning
- Experience implementing and optimizing ML workloads and low-level software algorithms for specialized hardware such as FPGAs, DSPs, DL accelerators.
- Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, BW and compute
- Experience with ML Models from definition to deployment including training, quantization, sparsity, model preprocessing, and deployment
- Proficient in Python development in Linux environment and using standard development tools
- Experience with deep learning frameworks (such as PyTorch, Tensorflow)
- Experience training, tuning and deploying ML models for CV (ResNet,..), NLP (BERT, GPT), and/or Recommendation Systems (DLRM)
- Experience deploying ML workloads on distributed systems
- Self-motivated team player with a strong sense of ownership and leadership
Desired:
- Research background with publication record in ML conferences such as ICML, NeurIPS, ICLR,...
- Prior startup, small team or incubation experience
- Work experience at a cloud provider or AI compute / sub-system company
- Experience implementing SIMD algorithms on vector processors
- Experience with open-source ML compiler frameworks such as MLIR
About Braves Technologies
Sourced by ZipRecruiter
Industry
It services
Company size
11 - 50 Employees
Headquarters location
Woodstock, GA, US
Year founded
2003