DevOps Engineer (Junior/Mid-Level) - Bazel Monorepo

Reposted 2 Days Ago
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Bristol, England, GBR
In-Office
Senior level
Semiconductor
The Role
Design, implement, and own Bazel rules and tooling to scale a multi-language monorepo (Python, C++, Rust, SystemVerilog). Build reproducible build pipelines, optimise CI across clusters, define developer experience, and contribute upstream to Bazel rules.
Summary Generated by Built In
DevOps Engineer (Junior/Mid-Level) - Bazel Monorepo

Fractile  ·  London or Bristol  ·  Full-time  

About Fractile

Fractile is building silicon, systems, and software that will redefine the frontier of AI — running the world's most advanced models at radically higher speed and lower cost. Founded in 2022, our 100+ person team spans hardware and software, and we're growing fast to deliver our product at scale.

We're an exceptional team working on an exceptional problem. If you want to build infrastructure that powers the future of AI computing, you'll fit right in.

The Role

We're looking for a Build Systems Engineer to own Bazel at Fractile and build the tooling that underpins every part of what we do — from ML models and kernel drivers to hardware simulation and compilers. This is a greenfield role: no legacy systems, no inherited constraints. You'll be designing the Bazel ecosystem from scratch in a fast-growing deep-tech company.

Your work will become the foundation every engineer at Fractile builds on. That's the scope, and that's the opportunity.

What You'll Work On
  • Design and own Bazel rules and extensions across the stack
  • Scale our monorepo as we grow across Python, C++, Rust, SystemVerilog, and ML workloads
  • Create reproducible, multi-language build pipelines
  • Optimise CI performance across large compute clusters
  • Define the developer experience for every engineer at Fractile
  • Contribute upstream to Bazel rules we depend on
Why This Role Stands Out
  • No legacy — you're building the Bazel ecosystem from scratch
  • Extreme variety — ML, compilers, kernel drivers, simulators, hardware verification
  • High impact — your work becomes the backbone of the entire engineering organisation
  • Deep collaboration with Simulation, Runtime, and Hardware teams
  • Real ownership — you shape how Fractile builds software
What We're Looking For

You'll be a strong fit if you have:

  • 5+ years in software or infrastructure engineering
  • 3+ years working with build systems
  • Strong hands-on experience with Bazel
  • Python scripting and automation skills
  • Experience with CI/CD for large-scale products

Bonus Points

These aren't requirements, but they'd make you stand out:

  • Experience with ML pipelines
  • GitHub Actions or similar CI tooling
  • Multi-language build systems
  • Container-based build environments
Why Fractile
  • Work on genuinely novel problems at the frontier of AI hardware
  • A collaborative culture built on curiosity, initiative, and technical depth
  • Hybrid working: 3 days onsite (London or Bristol), 2 days remote
  • Modern offices in London and Bristol — choose your base
  • Competitive salary and equity in a fast-growing company
Export Control & Security Clearance

Certain roles may involve working on technologies subject to export restrictions. Applicants may be required to undergo additional eligibility checks to ensure compliance with applicable law.

Fractile is committed to building a diverse and inclusive team. We welcome applications from people of all backgrounds and actively encourage candidates from underrepresented groups to apply.

Ready to apply? Send us your CV and a brief note on what excites you about this role.

Skills Required

  • 5+ years in software or infrastructure engineering
  • 3+ years with build systems
  • Strong experience with Bazel
  • Python scripting and automation
  • Experience with CI/CD for large-scale products
  • Experience with ML pipelines
  • GitHub Actions
  • Multi-language build systems
  • Containers
Am I A Good Fit?
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The Company
80 Employees
Year Founded: 2022

What We Do

Fractile is developing AI chips designed for efficient AI model inference, aiming to radically improve the speed and cost of running frontier AI models by eliminating memory bottlenecks.

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