Job Detail
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Job ID 6562
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Industry AI
Job Description
As an ML Systems Engineer at Symbolica, you’ll work side-by-side with researchers to build the infrastructure and tools that power our symbolic reasoning models. You’ll optimize training pipelines, debug performance issues, and enable fast, reliable experimentation—playing a critical role in scaling cutting-edge AI research.
What You’ll Do
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Build and optimize training pipelines (JAX, PyTorch) for symbolic ML models.
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Improve runtime, memory efficiency, and debugging on GPU clusters.
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Develop tools for model inspection, verification, and evaluation.
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Ensure reproducibility through versioning, config management, and experiment tracking.
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Translate research needs into scalable, maintainable systems.
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Support model serving and internal/external deployment infrastructure.
What You Bring
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Strong software engineering skills with experience in ML infra, HPC, or distributed systems.
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Proficiency in Python and deep learning frameworks (JAX or PyTorch).
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Experience with profiling, debugging, and scaling ML workloads.
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Familiarity with Docker, Kubernetes, and cloud/GPU infrastructure.
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Systems thinking: you streamline complexity and optimize performance.
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A collaborative mindset and interest in advancing symbolic AI research.
Why Symbolica
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Competitive salary + equity package.
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High-impact role accelerating frontier AI research.
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Work onsite at our London HQ (66 City Rd) with a top-tier team.
Required skills
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