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 productionDesign systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoningTrain and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scaleWork with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasksDevelop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategiesOptimize models for inference latency and throughput using techniques like distillation, quantization, and GPU accelerationRead current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production codeImplement efficient, scalable data pipelines and inference infrastructureDevelop high-performance tooling in ML and data engineeringRequirements:Experience building, training, evaluating, and deploying ML models in productionStrong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize modelsStrong software engineering ability to build and maintain complex systems and work with large-scale datasetsAbility to solve open-ended problems and quickly learn new domainsComfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraintsBS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experienceNice to have:Experience inferring structured, real-world attributes from imagesExperience training models on large-scale, real-world image datasetsFamiliarity with vision-language models (VLMs)Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production codeExperience building LLM or VLM pipelines and the evaluation frameworks to measure their performanceExperience in an ML role at a growth-stage startupPublications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)BenefitsMedical, Dental, Vision, STD and LTD PlansFSA - Medical and Dependent CareEAP and wellness programs13 Paid HolidaysUnlimited PTOFlexible work environment - 100% remote401(k) plan