ML Researcher

About Us

Base Compute is an AI inference lab. Our mission is to bring AGI on device. We believe in a world where everyone has access to intelligence: fast, private and always available on your device.

We’re building the infrastructure for the next generation of on-device AI, from silicon-level optimizations to distributed inference systems.

We’re working on hard problems at the intersection of inference efficiency, model intelligence and autonomous research.

The Role

We’re looking for a Founding ML Researcher to work at the frontier of on-device AI. This role is for someone who identifies problems and potentials, designs and executes experiments and derives insights that translate into real-world performance.

You’ll have significant ownership over our research agenda and direct influence on the technical bets the company makes.

What You’ll Work On

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Inference research: Identifying and validating new approaches to on-device efficiency, including speculative decoding variants, novel quantization schemes and entirely new techniques yet to be discovered

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Model routing research: Building the intelligence that decides how requests are served between on-device vs. frontier API models

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Autoresearch pipelines: Designing systems that can autonomously explore, hypothesize and evaluate research ideas that accelerate our R&D loop

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Evaluations and benchmarks: Developing rigorous evals that measure performance in the real world, outside of clean academic settings

What We’re Looking For

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PhD in ML or equivalent industry research experience

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Deep understanding of LLM architectures and the principles of AI inference

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Expertise in a relevant topic, such as speculative decoding, quantization theory, model distillation, reinforcement learning

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A track record of producing results that people build on: research papers, open-source projects or blog posts that prove out novel ideas

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Good communication: the ability to explain complex ideas simply, give honest feedback and document findings in a reproducible way

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Nice-to-haves:

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Familiarity with GPU and accelerator architectures and kernel optimization (CUDA, ROCm, Metal, Triton, etc.)

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Experience deploying models under on-device constraints (memory bandwidth, latency budgets, and thermal and power ceilings)

What We Offer

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Equity and strong base salary

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Direct influence on technical direction: your ideas will shape the roadmap

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Work on genuinely hard problems that haven't been solved yet

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Small team, fast iteration, low bureaucracy

Location

The team is based in Melbourne and Berlin and works in-person from the office most days. We require strong written and spoken English, since the team collaborates across time zones.

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