Artificial Intelligence Engineer

An AI research lab building high-quality multimodal datasets across video, audio, images, text, and 3D.They combine large-scale data infrastructure, multimodal understanding techniques, and proprietary data sources to create datasets used by leading AI labs to improve frontier foundation models.They are a small, fast-moving team where engineers work directly on production systems that influence model quality at scale.About the RoleThey’re looking for a Machine Learning Engineer to own ML problems end to end, from understanding customer needs and designing datasets to improving models, building evaluation systems, and shipping production pipelines.You’ll work directly with frontier AI teams on challenging problems involving model quality, dataset quality, evaluation, filtering, ranking, retrieval, and multimodal understanding.This role is a strong fit for an engineer who enjoys building production ML systems, experimenting with new models, and taking ambiguous problems from initial requirements through deployment.What You’ll Work OnBuild and improve production machine learning systems in PythonTrain, fine-tune, and deploy modern deep learning and foundation modelsDevelop evaluation and QA pipelines using models such as GPT, Claude, Gemini, and open-source modelsDesign systems for filtering, ranking, retrieval, labeling, and dataset curationBuild benchmarks and evaluation frameworks for model and dataset qualityAnalyze precision, recall, edge cases, and failure modes to improve system performanceDevelop scalable ML pipelines spanning preprocessing, inference, post-processing, and quality validationWork directly with customers and cross-functional teams to translate complex requirements into production systemsRapidly prototype with new models, tools, and APIsRequirements2+ years of relevant experienceStrong Python engineering skillsExperience building and shipping production machine learning systemsExperience training, fine-tuning, or deploying modern deep learning modelsHands-on experience with PyTorchExperience working with modern foundation modelsStrong understanding of model evaluation, dataset quality, precision and recall tradeoffs, and edge casesAbility to own technical projects from problem definition through deploymentStrong communication skills and comfort working with customers and cross-functional teamsAble to work onsite at Sieve’s San Francisco office 5 days per weekNice to HaveExperience with computer vision, video understanding, or multimodal AIExperience with vision-language models or other multimodal foundation modelsExperience building large-scale data or ML pipelinesExperience with data filtering, curation, ranking, or retrieval systemsExperience rapidly prototyping with new AI models and APIsBackground at an AI company, ML infrastructure company, data platform, or high-scale engineering organizationJob DetailsLocation: San Francisco, CA Workplace: Onsite, 5 days per week Employment Type: Full-time Experience: 2+ years Compensation: $150,000–$350,000 per year Equity: Competitive equity Visa Sponsorship: Not available Benefits: Health insurance