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Salary
$143k – $309k per year (Estimated)
Location
Remote (United States)
Employment
Full-Time
Overview
Company
Impact
Profile match

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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