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    Job · 16738813

    Theta logo

    AI Backend Engineer

    Theta · Not specified · onsite · Posted 77d ago

    Not disclosed6–9 yrsfulltimeSourced fromInstahyre

    About a minute. You'll make an account on the way through.

    About this role

    We are looking for a Founding Engineer with 5-9 years of experience to join Theta as one of the earliest engineering hires, bringing deep backend infrastructure and AI/ML expertise to a team solving some of the hardest data and systems problems in frontier AI. You'll be a mature, highly autonomous IC who elevates the entire engineering org with hard-won experience from deeply technical environments.


    Responsibilities:

    • Work directly with founders across engineering, product, and operations to define priorities and execution strategy.
    • Own and scale core backend infrastructure powering Theta's data platform, managing cloud compute, optimising workers, and solving hard systems problems daily.
    • Tackle research-grade engineering challenges at the intersection of AI, agents, and data pipelines, implementing new model harnesses and staying ahead of the frontier.
    • Build and improve internal tooling and workflows that maintain high-fidelity, high-quality data output at scale.
    • Work directly alongside founders to define technical priorities and drive execution with minimal oversight.
    • Bring engineering maturity and hard-earned instincts to a small, fast-moving team raising the bar for how problems are scoped and solved.
    • Understand domain workflows and translate them into agent training environment tasks.


    Requirements:

    • 5-9 years of experience at a deeply technical company (e. g., AI/ML-focused team at a top-tier startup or FAANG) where you've been solving infrastructure problems most engineers haven't encountered.
    • Strong backend infrastructure background: cloud compute management, distributed systems, worker optimisation, and scaling platforms under real load.
    • Hands-on experience with AI/ML systems, whether on an agent, post-training, or ML infra team, or building ML-adjacent infrastructure (not recommendation systems, ad ranking, or traditional ML pipelines).
    • Genuine, innate interest in the AI tooling landscape; you follow new model releases, harnesses, and frameworks closely and move fast to apply them.
    • High autonomy and scrappiness: you thrive in ambiguous, fast-moving environments and don't need hand-holding to ship.

    Sourced from instahyre

    Skills

    Distributed SystemsComputer Visionamazon web servicesNatural Language ProcessingDjango FrameworkLarge Language Models (LLMs)PythoncloudAgentic AiGenerative AiMachine Learninggoogle cloud platformdistributedscalingcomputeBackendInfrastructureArtificial Intelligence

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