Über
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In-person | San Francisco Our client is building high-performance systems to understand video at internet scale. Video now accounts for ~80% of internet traffic and is rapidly becoming the foundation for creativity, communication, gaming, AR/VR, and robotics. The limiting factor in next-generation AI isn’t models — it’s
high-quality video data and understanding at scale . This team sits at the intersection of: Computer Vision Audio + speech processing Multimodal AI systems Large-scale data infrastructure Their mission is to transform raw video into structured, usable datasets and systems that unlock frontier model performance. The role As an Applied Research Engineer, you’ll design and build systems that power large-scale video understanding. You’ll work across both research and production, including: Building high-performance data and inference pipelines Improving model performance through smart preprocessing and optimisation Working with APIs, models, and multimodal systems Solving ambiguous, research-heavy engineering problems Shipping end-to-end systems that directly impact customers and model capability What they’re looking for 2+ years experience in Computer Vision or Audio ML Strong Python engineering skills Experience with PyTorch or similar ML frameworks Ability to work across research + production environments Strong communication skills with technical and non-technical xywuqvp stakeholders Clean, production-quality coding practices Ability to translate customer problems into technical system design Passion for video, media, or multimodal AI systems Bonus Open-source contributions Early-stage startup experience Portfolio of applied ML or systems work Must be based in or willing to work in-person in San Francisco. If you’re interested in building systems that turn video into intelligence at scale, our client would like to hear from you.
Sprachkenntnisse
- English
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