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. 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 Requirements: Experience building, training, evaluating, and deploying ML models in production Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models Strong software engineering ability to build and maintain complex systems and work with large-scale datasets Ability to solve open-ended problems and quickly learn new domains Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience Nice to have: Experience inferring structured, real-world attributes from images Experience training models on large-scale, real-world image datasets Familiarity with vision-language models (VLMs) Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance Experience in an ML role at a growth-stage startup Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV) Benefits Medical, Dental, Vision, STD and LTD Plans FSA - Medical and Dependent Care EAP and wellness programs 13 Paid Holidays Unlimited PTO Flexible work environment - 100% remote 401(k) plan Clearview AI