Senior Applied AI/ML Engineer - confido

Confido is the AI infrastructure powering modern CPG — the platform that 200+ brands like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana use to run everything from deductions to production planning. Finance, accounting, sales, and operations, unified in one system for the first time.

We're growing 5x year over year and recently raised a $15M Series A led by Footwork and Y Combinator. We're a small, in-person team in New York City, which means the people who join now shape the product, the culture, and the company itself.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

THE ROLE

Build the core AI behind Confido — and get your hands on an unusually rich, messy dataset: hundreds of thousands of documents across dozens of sources and hundreds of layouts and contexts, much of it beyond what any system reads well today.

As a Senior Applied AI / ML Engineer, you'll own AI problems end to end — research, prototyping, production, and the evaluation that keeps probabilistic systems reliable — across document understanding, forecasting, and agentic workflows.

Location: New York, NY (Relocation supported)

WHAT YOU'LL DO

• Build LLM systems that turn complex, inconsistent financial documents into clean, typed, validated data — the backbone the rest of the platform runs on
• Design agentic workflows that retrieve and reason over fragmented enterprise systems, with the eval harnesses and guardrails to run them in production
• Build and improve demand forecasting across thousands of intermittent series — classical time-series and gradient-boosted models, with rolling-origin backtesting and best-fit selection
• Wrangle messy, real-world data: baselining, outlier and anomaly detection, entity reconciliation, and ingestion across heterogeneous sources
• Own how we measure success — eval datasets, benchmarks, and monitoring for systems with no single "correct" answer

WHAT WE'RE LOOKING FOR

Required

• 5+ years of applied AI / ML, with systems you've taken to production (not just prototypes)
• Depth in at least one, and working fluency across several, of: time-series / forecasting and statistical modeling; LLM and agentic systems; large-scale messy-data engineering
• You build evaluation and monitoring as a matter of course — and know which metric to trust, and how to avoid leakage and train/serve skew
• Strong product sense: you turn AI capability into real outcomes, and know when a simpler approach wins

Nice to have

• Demand forecasting / time-series (Prophet, ARIMA-family, gradient-boosted)
• Agentic workflows, RAG, or retrieval systems in production
• Document understanding / information extraction from unstructured sources