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Senior Applied AI/ML Engineer

Confido · On-site

This listing is no longer verified as available.

MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

Source: the employer's Ashby job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
On-site
Salary
Not listed by source
Location
NYC Office

What the role asks for

What you'd 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
  • 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

What they're asking for

  • Demand forecasting / time-series (Prophet, ARIMA-family, gradient-boosted)SkillPreferred
  • Agentic workflows, RAG, or retrieval systems in productionSkillPreferred
  • Document understanding / information extraction from unstructured sourcesSkillPreferred
  • Startup experience or comfort in fast-moving environmentsSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

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 with a small team in New York City; the people who join now will 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 - Startup experience or comfort in fast-moving environments 🌴 PERKS + BENEFITS - Equity - own a meaningful piece of the company you’re helping build - Fully paid health coverage through Aetna - we cover 100% of employee premiums - Top-tier dental and vision coverage through Guardian - Carrot Fertility Pro - comprehensive fertility and family-forming support - 12 weeks of paid parental leave - Unlimited PTO - plus regular 4-day holiday weekends we actually take - 401(k) through Vestwell - Paid relocation support - we’ll help you make the move to NYC - Fully equipped workspace from day one - laptop, monitor, keyboard, and a $200 stipend to personalize your setup - Team perks - catered Friday lunches, team dinners, and unlimited coffee + snacks featuring products from the brands we work with Confido provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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