ashby
Software Engineer - ML Infrastructure
Specter
San Francisco, USA
Full-time
Mid
Onsite
Discovered 1 months ago
PyTorchTensorFlowTensorRTONNX RuntimeOpenVINOWeights & Biases
Key Skills for This Role
PyTorchTensorFlowTensorRTONNX RuntimeOpenVINOWeights & Biases
Full Job Posting
Role + Responsibilities
- Specter is hiring an ML infrastructure engineer to build and scale the machine learning systems that power real-time perception and inference across our edge-cloud platform. This role owns the training, deployment, and optimization of computer vision and sensor fusion models that enable autonomous monitoring and decision-making for our customers' physical assets.
Key responsibilities include
- Designing and implementing scalable ML training pipelines for computer vision models (object detection, tracking, classification, segmentation).
- Building efficient model serving infrastructure for real-time inference on edge devices with constrained compute and power budgets.
- Optimizing models for deployment on embedded hardware (quantization, pruning, TensorRT, ONNX, CoreML).
- Developing continuous training and evaluation systems to improve model performance from production data feedback loops.
- Creating data pipelines for ingesting, labeling, versioning, and managing massive multi-modal sensor datasets (video, radar, lidar, thermal).
- Implementing model monitoring, A/B testing frameworks, and performance analytics for deployed perception systems.
- Collaborating with perception researchers to transition models from research to production at scale across thousands of edge nodes.
- Building tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.
Preferred Qualifications
- Strong experience with ML frameworks (PyTorch, TensorFlow) and model optimization tools (TensorRT, ONNX Runtime, OpenVINO).
- Deep understanding of computer vision architectures and their deployment tradeoffs (YOLO, transformers, CNNs, real-time detection/tracking).
- Hands-on experience deploying models on edge devices (NVIDIA Jetson, ARM processors, or similar embedded platforms).
- Expertise building MLOps infrastructure — experiment tracking (Weights & Biases, MLflow), feature stores, model registries, CI/CD for ML.
- Experience with distributed training frameworks (PyTorch DDP, DeepSpeed, Ray) and GPU cluster management.
- Strong software engineering skills in Python and systems languages (C++, Rust) for performance-critical inference code.
- Familiarity with video processing, sensor fusion, or multi-modal perception systems is a plus.
- Prior experience in robotics, autonomous systems, or real-time ML applications is highly valued.
About Specter
Electronics ManufacturingFounded 2025
Specter is a private San Francisco company building AI-powered video sensors and wireless networks for industrial businesses.
Visit company websiteJobs and hiring trendsApply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career
More from this employer
More jobs at Specter
Business Operations Generalist
San Francisco, USA
Discovered 3 days agoFull-time
Optics & Camera Engineering Lead
San Francisco, USA
Discovered 1 weeks agoFull-time
CV/ML Camera Test Engineer
San Francisco, USA
Discovered 1 weeks agoFull-time
Founding Customer Operations Lead
San Francisco, USA
Discovered 2 weeks agoFull-time
ML Research Engineer
San Francisco, USA
Discovered 1 months agoFull-time
RF Systems Engineer
San Francisco, USA
Discovered 1 months agoFull-time
Software Engineer - Full Stack
San Francisco, USA
Discovered 1 months agoFull-time
Deployment Operations Engineer
San Francisco, USA
Discovered 1 months agoFull-time