Applied AI/ML Engineer — Equity & Impact in Enterprise AI

Confido Health, Inc.; New York (NY); Vor Ort; USD 150.000 - 230.000; Vollzeit

Benefits dieser Stelle

Equity

Health coverage

Dental & Vision

Fertility support

Parental leave

Unlimited PTO

401(k)

Relocation support to NYC

Workspace stipend

Team events

Zusammenfassung

Confido Health, Inc. is building the AI operating system powering cash application, deductions, trade, and planning for top CPG brands.

We seek an Applied AI / ML Engineer to own problems end to end—from research and prototyping to production and evaluation—in data-rich, real-world settings in New York, NY (relocation supported). You will develop LLM-based systems, design agentic workflows, and advance time-series forecasting while wrangling large heterogeneous datasets.

Qualifikationen

• 3+ years of applied AI/ML with production experience.
• Masters degree in STEM mandatory.
• Strong product sense and ability to translate AI capabilities into outcomes.

Aufgaben

• Build core AI behind Confido across document understanding and forecasting.
• Prototype, productionize, and evaluate probabilistic systems.
• Design agentic workflows and integration with enterprise systems.
• Wrangle real-world data, perform baselining, anomaly detection, and entity reconciliation.
• Define eval datasets, benchmarks, and monitoring for ongoing reliability.

Kenntnisse

Applied AI/ML in production

Time-series forecasting

LLM & agentic systems

Messy-data engineering

Evaluation & monitoring

Ausbildung

Masters degree in STEM

Jobbeschreibung

Confido Health, Inc. is building the AI operating system powering cash application, deductions, trade, and planning for top CPG brands.

We seek an Applied AI / ML Engineer to own problems end to end—from research and prototyping to production and evaluation—in data-rich, real-world settings in New York, NY (relocation supported). You will develop LLM-based systems, design agentic workflows, and advance time-series forecasting while wrangling large heterogeneous datasets.