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Stuut

Member of the Technical Staff — AI/ML

1 day ago by Stuut
  • Salary negotiable
  • San Francisco, CA, US
  • Full-time
Typical response: within 5 days Secure 1-click apply No spam — we never sell your data
AI summary

Hands-on Member of the Technical Staff (AI/ML) role building and deploying production AI systems and agentic LLM features for B2B accounts receivable workflows (invoice matching, payment reconciliation, document processing). Stuut is a venture-backed fintech/B2B SaaS platform modernising collections for industrial and manufacturing finance teams. Standout perks include top-of-market salary and equity plus full US benefits and 401(k) match.

Key skills
PythonLLMs and RAG systemsFine-tuning on proprietary dataTool-using LLM agents (planning/state/recovery, human-in-the-loop)MLOps (deployment, monitoring, A/B testing, versioning)AI/ML evaluation (golden datasets, offline/online evals, CI regression testing)PyTorchTransformersscikit-learnXGBoost
Salary not listed — “top-of-market salary and equity”; comparable San Francisco MTS AI/ML roles often pay roughly $200k–$350k base plus equity depending on level and experience.
You'll thrive here if you’ve shipped production agentic AI/LLM systems end-to-end and enjoy turning AI research into reliable, measurable improvements for real financial operations workflows.
Why apply
  • Top-of-market salary and equity
  • 401(k) & match
  • Medical, dental & vision insurance
Stuut is transforming accounts receivable for B2B companies—making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We're backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures and Page One. The Role We’re hiring a Member of Technical Staff – AI/ML to design, build, and deploy AI-powered systems that solve real-world financial operations challenges. You’ll take state-of-the-art AI research and translate it into production-grade features that deliver measurable customer impact. From intelligent invoice matching to automated payment reconciliation, you’ll create scalable, reliable AI applications that integrate seamlessly into our platform. This is a hands-on role for an engineer who thrives at the intersection of AI innovation and practical business application — turning cutting-edge models into real-world value for midmarket CFOs What You’ll Do Create production-ready AI applications and agentic systems that address customer financial workflow challenges Build tool-using LLM agents that surface insights, recommend next steps, and execute approved tasks — not just chatbots Refine capabilities like invoice matching, payment reconciliation, and financial document processing Apply and optimize LLMs and RAG systems for financial use cases, including fine-tuning on proprietary data where it moves the needle Build robust AI pipelines from ingestion to inference — reliable, maintainable, and cost-efficient through smart model routing Stand up golden datasets, agent tracing, regression-on-PR, and A/B testing so we ship confidently and catch silent regressions Partner with Product, Engineering, Data, and customers to translate business needs into AI solutions Treat every AI feature as a continuously-improving system — instrument everything, iterate You Might Be a Fit If You… Have 5+ years of AI/ML experience Have shipped agentic products in production and understand the failure modes (tool use, planning, state, recovery, human-in-the-loop) Have integrated and fine-tuned LLMs, and built RAG systems for document- or data-intensive workflows Have trained and deployed classical ML models (risk scoring, forecasting, ranking, or similar) — feature engineering, model selection, evaluation, calibration Have strong opinions on AI/ML evals — golden datasets, offline + online evaluation, statistical significance, evals in CI Are familiar with LLM observability tooling (LangSmith, Braintrust, Arize, or similar) and treat tracing as table stakes Understand MLOps fundamentals: deployment, monitoring, A/B testing, model and prompt versioning, feature stores Are fluent in Python and modern AI/ML tooling (PyTorch, Transformers, scikit-learn, XGBoost, vLLM, LangChain/LlamaIndex, or equivalent) Have shipped AI/ML products that solved real business problems, not just prototypes Can translate business requirements into clear technical solutions Bonus: experience with model routing across providers Bonus: fintech, B2B SaaS, or AR/AP domain experience Are plugged into the AI/ML community and energized by bringing AI to real-world use cases Compensation Top-of-market salary and equity package Benefits (for U.S.-based full-time employees) Medical, dental & vision insurance coverage for you 401(k) & Match Equity Flexible PTO Parental Leave

Reference: 22598_2659927438·Original posting
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