Entrepreneurial AI Researcher

Deeter Analytics

  • 30+ days ago

    Highlights

    Follow Ideas to PoC to MVP to training to validation, owning all steps of the process with deep collaboration with Research Engineers (see other open role). -Are a self-starter who thrives on coding autonomy and project collaboration within small-team, high velocity environments.

    Numbers & Facts

    Location
    Websitehttps://deeteranalytics.com

    Description

    Join a small, fast-moving team where you’ll explore, invent, and discover.
    We’re training foundational models for financial applications on unique, multimodal datasets.

    What you’ll do


    -Formulate and pursue original research agendas (reasoning, tool connectivity, robustness, alignment, data/compute efficiency).
    -Follow Ideas to PoC to MVP to training to validation, owning all steps of the process with deep collaboration with Research Engineers (see other open role).
    -Build rigorous evaluation suites through simulated environments and real time evaluation.
    -Prototype fast with real data; partner with Research Engineers to take promising ideas to production.

    You might be a fit if you


    -Are a self-starter who thrives on coding autonomy and project collaboration within small-team, high velocity environments.
    -Have strong ML research chops (theory and practice), and write clean, reproducible code (e.g. PyTorch/JAX).
    -Think in systems: data quality, scaling laws, evaluation, and deployment constraints - not just model internals.
    -Prefer clear principles, low ego and prefer collaboration over titles and politics. Helpful backgrounds (any of the following)

    -Frontier labs experience (e.g., Anthropic, OpenAI, DeepMind); or

    -Novel discovery through published work (NeurIPS/ICML/ICLR); or

    -Led research in an applied setting (startups, open-source, or products at scale); or

    -Standout independent achievement (notable OSS, benchmarks, or widely used methods).

    Research areas we’re excited about


    -Efficient training (HRM, distillation, sparse/MoE, FSDP, etc.).
    -Reasoning and tool use (automated trading and agentic interaction with data sources).
    -Multimodal Inputs and Outputs (multiple forms of text and time-series both in and out).

    What we offer


    -A well-funded trading firm expanding into AI research - your ideas set direction and standards.
    -Real ownership from hypothesis to deployment.
    -Competitive base with meaningful upside tied to research impact.
    -A culture optimized for deep work, fast learning, and doing the right thing.

    If this sounds like you, apply.

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