Research Engineer

Описание вакансии

Research Engineer

Full-time/Company: Gauntlet

Gauntlet builds the financial systems of the future, operating across the onchain finance stack and serving institutional clients with best-in-class vault products. They support over $1.7B in client TVL across fintechs, protocols, exchanges and traditional asset managers.

Applicants must be able to work within the contiguous United States and Canada.

Responsibilities:

• Build evaluation frameworks for AI agents, including datasets, sandbox environments and metrics for real-world tasks.
• Design experiments to compare models, agent harnesses, tools and execution environments to identify regressions and trade-offs.
• Turn qualitative feedback about agent behaviour into concrete research questions, experiments and measurable outcomes.
• Investigate agent failures to determine root causes (model, harness, tooling, prompting) and improve performance.
• Build and improve agent harnesses, internal tools and integrations, including contributing to Aria and other agents.
• Develop shared knowledge and reusable skills across agents so systems can learn and improve over time.
• Collaborate with Infrastructure and Security to ensure agents operate reliably and safely in production.

Requirements:

• Hands-on experience building, evaluating or improving LLM models or agents (professional, research, open-source or personal projects).
• Strong Python skills and solid software engineering fundamentals; able to write production-quality, tested code.
• Experience with applied research, machine learning or data science, including experiment design and dataset work.
• Understanding of how LLM agents work beyond prompting: tool use, harnesses, context management and failure modes.
• Ability to decompose open-ended problems into testable questions and work independently toward solutions.
• Experience building tools or systems for other teams, with attention to evaluating effectiveness beyond benchmarks.
• Comfortable collaborating across research and engineering and adapting to changing priorities.

Nice to have:

• Experience building LLM evaluation pipelines, benchmarks, RL environments or model testing infrastructure.
• Contributions to open-source agent frameworks, harnesses, evaluation datasets or benchmarks.
• Experience with agent frameworks such as Hermes, OpenClaw or similar tools.
• Experience in applied ML research, model training, fine-tuning or reinforcement learning.
• Advanced degree or postgraduate research experience in CS, mathematics, statistics, ML or related field.
• Experience in financial markets, quantitative research, DeFi or risk modelling.
• Familiarity with AI security considerations, including access controls, prompt injection and data protection.

Stack:

Python, LLMs, agent frameworks (Hermes, OpenClaw), reinforcement learning, fine-tuning

Benefits:

• Remote first — work from anywhere in the United States
• Regular in-person company retreats and cross-country "office visit" perk
• 100% paid medical, dental, and vision premiums for employees
• $1,000 WFH stipend
• Monthly reimbursement for home internet, phone, and cellular data
• Unlimited vacation
• 100% paid parental leave of 12 weeks
• Fertility benefits
• Opportunity for incentive compensation
• National pay range: $175,000 - $195,000 base plus additional On Target Earnings potential and equity

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