Member of Technical Staff - Applied ML

About the Role

This is an applied ML engineering role at a Series B fintech company building agentic AI for accounting professionals. You'll own end-to-end projects — from architecture through production — designing the systems that help intelligent agents reason, plan, and evaluate themselves at scale. The work sits at the intersection of research-minded thinking and pragmatic engineering, and your output will directly shape how accounting workflows become smarter and more autonomous.

What You'll Do

• Design and iterate multi-agent architectures that automate real-world accounting workflows end-to-end.
• Encode autonomy boundaries, tool usage, and fallback behaviors to keep agents safe, reliable, and auditable.
• Manage context and memory across multi-step agent loops with clearly defined success criteria.
• Route, evaluate, and optimize model usage under production constraints including latency, cost, and accuracy.
• Build scalable evaluation pipelines — offline and online — capable of running hundreds of experiments automatically.
• Define golden tasks, labeling strategies, and metrics that make model and product performance measurable and comparable.
• Instrument the stack to detect regressions, track error taxonomies, and drive closed-loop improvement.
• Architect prompt stacks and retrieval pipelines; parse messy documents into structured representations for reasoning.
• Design guardrails and validation layers to keep agent behavior safe and deterministic.

What We're Looking For

• 3+ years of AI/ML engineering experience building production systems or AI applications.
• Deep expertise in Python and LLM/transformer-based systems.
• Hands-on experience building end-to-end LLM-based agent applications including model orchestration, benchmarking, and evaluation frameworks.
• Experience designing and running structured ML experiments — hypothesis framing, evaluation infrastructure, and iteration on measurable results.
• Experience building retrieval and indexing pipelines; familiarity with parsing unstructured documents into structured representations.
• Background at a fast-paced startup, top-tier tech or AI-native company, or quantitative finance environment.
• Strong CS fundamentals; a degree in CS, Math, Physics, or a related technical discipline.
• Clear, concise communicator who can break complex concepts down to first principles.
• Interest in AI applications within accounting, finance, or economic systems is a plus.

Compensation & Benefits

Salary range: $175,000 – $300,000 USD annually. Visa sponsorship is available.

Location

On-site, five days a week in Los Angeles, CA. Candidates currently located in the US or Canada preferred.