A 2021 VC backed startup is transforming the patent system using AI, handling every patent document ever created (15+TB of data and 500M+ embeddings). We’re looking for a Senior Software Engineer to own the data and machine learning infrastructure.
What You’ll Do:
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Build and maintain scalable ML infrastructure and data pipelines.
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Handle massive vector databases and embeddings (≥500M vectors).
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Architect distributed systems that process 20M+ API requests daily.
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Optimize cloud infrastructure on Google Cloud for performance and cost.
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Own end-to-end ETL and ML pipelines processing multi-TB datasets.
Tech Stack:
Python | GCP | Postgres / pgvector | Kubernetes | Celery | RunPod | CUDA
Why Join:
- Work with massive, industry-defining datasets.
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Be part of an early-stage startup with high exit potential.
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Join a non-toxic, flexible culture (flexible & empathetic Founders, no weekend crunch).
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Competitive salary $250K + equity, with the opportunity to shape the future of legal tech.
Who You Are:
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5–12 years of experience in backend, data, or ML infrastructure engineering (with GCP).
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Proven track record scaling and optimizing distributed systems / ML infrastructure.
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Experienced in GPU training, CUDA debugging, and cloud cost optimization.
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CS degree from a top 20 university preferred.
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Enjoys end-to-end ownership in early-stage startups, not just big-tech specialisation.
Apply now if you’ve built ML pipelines at scale and want ownership of infrastructure that powers cutting-edge AI.
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