Senior Machine Learning Engineer

United States·WashingtonFull Timesenior

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

Build, train, evaluate, and deploy computer vision and multimodal models,

Technical Tools

Machine Learning EngineerData

Clearview AI is the leading provider of facial recognition technologies to US law enforcement, state, and federal agencies. Our mission is to help our users solve crimes and prevent financial fraud with the responsible use of our facial recognition software. Our company is a high-octane, fast growing startup looking to hire enthusiastic and intelligent team members to join our team. To learn more about us, and our revolutionary facial recognition technology, please visit www.clearview.ai.

Senior Machine Learning Engineer

Position Summary: We are hiring a highly technical individual contributor to push the limits of our computer vision and machine learning capabilities. This is a high-impact, hands-on role for a research-minded engineer who wants to build and ship models, not manage a team. Much of the work involves large-scale visual understanding, extracting structured signals from imagery and reasoning about the real-world context behind a photograph, but we care more about deep ML/CV ability than any one problem area and welcome strong generalists.

Responsibilities:

Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production
Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning
Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale
Work with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks
Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies
Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration
Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code
Implement efficient, scalable data pipelines and inference infrastructure
Develop high-performance tooling in ML and data engineering
Additional duties and responsibilities as reasonably required by the employee’s supervisor or CEO