Hiring: Member of Technical Staff, Applied Research Company: Sieve Location: San Francisco, CA Job Posted Time: 2026-09-15 17:57:30 Employment Type: Full-time Target Skills & Keywords: Machine Learning Research, Multimodal Models, Video Generation, Audiovisual Understanding, PyTorch, Python, Diffusion Models, Transformers, Distributed Training, Fine-Tuning, Post-Training, Data Curation, Experiment Design, Model Evaluation, Generative AI Experience: - 2+ years of experience in machine learning research or engineering - Hands-on experience training or fine-tuning deep learning models - Experience designing experiments, establishing baselines, and evaluating results critically - Comfortable working with large datasets and diagnosing training bottlenecks, instability, and data quality issues Required Skills: - Strong Python and PyTorch skills, including the ability to implement, debug, and modify model training code - Familiarity with modern generative or multimodal architectures, such as diffusion models or transformers - Ability to turn ambiguous research questions into concrete experiments and maintainable systems - Strong communication skills and the ability to explain findings, tradeoffs, and uncertainty clearly - Experience developing reliable training infrastructure, including distributed training, efficient data loading, checkpointing, and experiment tracking Qualifications: - Train and post-train models for video generation and multimodal understanding - Design controlled experiments to measure how data selection, mixtures, and supervision affect model capabilities - Build evaluations that reveal specific model weaknesses, using quantitative metrics and human judgment - Turn research findings into improvements in data curation pipelines and products - Collaborate with research and engineering teams internally and at partner labs to define meaningful problems and communicate results - Bonus: Experience training video, image, or audio generation models - Bonus: Experience with supervised fine-tuning, preference optimization, or reinforcement learning - Bonus: Experience with distributed training and GPU performance optimization - Bonus: Research publications, open-source contributions, or substantial independent ML projects - Bonus: Experience as an early hire at a startup - All roles require onsite work in San Francisco 5 days per week Compensation: - Base pay range: $150,000.00/yr - $350,000.00/yr - 401k + Full Health Insurance - Breakfast, Lunch, and Dinner covered, plus your choice of snacks - Ubers covered home Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don’t miss this opportunity to join a forward-thinking team!