At Tilde Research, our mission is to build moonshot, applied interpretability solutions. We believe that by fundamentally understanding models, we can unlock paradigm shifts in throughput, performance, and safety. Our approach is to innovate across the entire stack, from uncovering the fundamental building blocks of model computation to enabling the precise steering of their behavior. We are driven by the conviction that true progress in interpretability will allow us to make AI more reliable and capable.
About the role:
As a ML Engineer, you’ll build and operate the infrastructure that makes cutting-edge machine learning research possible. At Tilde, we believe meaningful progress in AI requires not just novel ideas, but the ability to rapidly test, scale, and iterate on them—and that demands exceptional engineering.
You’ll work on the systems that support training and evaluating large models, scaling experimental pipelines, and building the infrastructure necessary to actually understand models. Your work will be foundational to our research, making it possible to explore ambitious ideas that push the boundaries of performance, interpretability, and control.
What you might work on:
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Optimize inference and training throughput for novel model architectures
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Build and maintain high-performance distributed training infrastructure
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Collaborate with researchers to translate insights into measurable improvements in model performance and understanding
You’re a good fit if you:
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Have experience in deep learning or related research areas
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Communicate clearly and effectively, both verbally and in writing
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Can come up with and evaluate research ideas
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Are able to learn quickly
