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    Job · 21328748

    BENGALURU · FULLTIME

    AI Research Engineer

    Sparkinity

    Sparkinity

    Bengaluru · onsite · Posted 5d ago

    Sourced fromInstahyre
    Not disclosed2–6 yrsfulltimeBengaluru

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    Section · 01

    About this role

    We're seeking an AI Research Engineer to own model evaluations end-to-end, turning ambiguous capabilities into rigorous, reproducible benchmarks. Working closely with researchers, you will design datasets, analyze model behavior at scale, and directly shape the training lifecycle.


    Responsibilities:

    • Design rigorous benchmarks for reasoning, coding, and agentic capabilities across C/C++, Rust, embedded systems, hardware specifications, and engineering tasks.
    • Develop deterministic evaluators using compilers, emulators, simulators, static analysis, formal verification, and hardware-in-the-loop systems.
    • Build distributed infrastructure to run evaluations reliably against models and live training checkpoints.
    • Diagnose regressions and anomalous results, separating model failures from issues in prompts, data, evaluators, or infrastructure.
    • Design robust metrics, difficulty curricula, contamination-resistant tasks, and experiments around prompting, sampling, and scaffolding.
    • Turn evaluation failures into targeted datasets, reward signals, and new training objectives in collaboration with RL researchers.
    • Create dashboards, experiment tracking, and evaluation libraries that make model performance easy to understand and trust.
    • Own the development of cutting-edge infrastructure from day one.
    • Solve complex engineering challenges that directly shape our product roadmap.
    • Accelerate your career alongside elite researchers in a fast-paced environment.
    • Work closely with a brilliant, collaborative team of industry pioneers.


    Requirements:

    • Strong Python programming and software engineering fundamentals.
    • Experience building benchmarks, evaluation systems, automated graders, research infrastructure, or similar testbeds.
    • Strong understanding of LLMs and modern evaluation methodologies.
    • Strong analytical and experimental thinking; you care deeply about whether a metric actually measures the intended capability.
    • Experience debugging complex systems and investigating unexpected experimental results.
    • Strong written and verbal communication.

    Sourced from instahyre

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    Section · 02

    Skills

    Agentic Ai

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