AI engineer (personal shopping memory & agents) @Nora
Part engineer, part product thinker, part hacker. 100% user obsessed
Full-time or Contract, Remote or NYC, $100K - $150K + Equity
ContextWe're building Nora, the personal shopping retriever loyal only to you.
Online shopping gave us infinite choice but zero tools to manage it. So people improvise with 47 browser tabs, screenshots flooding their camera roll, and links texted to themselves. They're drowning in options, missing price drops, and spending hours on research that leads nowhere.
Nora changes everything. Your personal shopping assistant that captures what you browse, what you buy, tracks prices, finds alternatives, verifies reviews, and soon will even negotiate deals on your behalf. All while keeping your data private and eventually earning you money.
Why this matters: We're shifting power back to consumers. For the first time, shoppers will have an AI assistant as sophisticated as what billion-dollar companies use. When you ask "Should I buy this?" Nora actually knows your style, budget, and what you've been considering.
Where we are: Just raised $750K from Betaworks & angels. Small team moving fast. Building something people desperately need. We’ve built the capture → memories → knowledge pipeline; now we need someone to make it truly smart and to power the agents that work on the user’s behalf.
Watch https://www.youtube.com/watch?reload=9&v=yULgS3qRWOA for more info.
The Real JobYou'll be the bridge between messy real-world shopping behavior and an assistant that actually understands and works for each user.
This isn't about research in a vacuum or building an internal ML platform. You'll be:
- Turning noisy data (DOM, clicks, scrolls, screenshots, receipts) into clean, structured memory about each shopper.
- Teaching Nora everything from “what brands I love” to “my shoe size at different stores” to “what price I consider expensive.”
- Building agents that go do the work: finding better places to buy, researching alternatives, checking reviews, and surfacing what matters.
- Shipping intelligence that shows up as real product features, not just dashboards.
Your success = shoppers saying “Nora knows me and does the boring work for me.”
What You'll Actually Do Day-to-DayBuild Nora’s Understanding of Each User- Model user tastes, sizes, favorite brands, and price sensitivity from behavior.
- Use LLMs and embeddings to turn raw capture into entities, attributes, and preferences.
- Improve our capture → memories → knowledge pipeline so it gets cleaner, richer, and more personal over time.
Build Nora’s Agents- Design agents that can:
- Find alternative places to buy the same product.
- Suggest similar items that better match the user’s constraints.
- Check reviews and flag sketchy listings.
- Track meaningful price changes and surface them at the right time.
- Wire LLMs to tools and structured data so agents are fast, reliable, and explainable.
Ship Product, Not Just Models- Work directly with the founder, designer, and Head of User Love (no PM layer).
- Watch real users shop with Nora, then adjust models and agents based on what you see.
- Prototype quickly, run small experiments, and ship improvements weekly.
- Own the full loop: data → model → API → UI → metrics.
You're Our Person If...You've Done This Before (In Some Form)- 2–8+ years working in applied ML / LLMs / search / recommendations / personalization.
- Shipped at least one real system that powered search, recs, ranking, or an LLM-based feature in production.
- Comfortable with both modeling and the surrounding engineering (data pipelines, APIs, evaluation).
You Think Like This- “We should measure success in user behavior, not just offline metrics.”
- “We don’t need a bigger model yet—just better features and feedback loops.”
- “Let’s prototype this as a small agent flow and then harden what works.”
You Work Like This- Comfortable with ambiguity (we’re figuring this out together).
- Can go from idea → prototype → shipped experiment in days, not quarters.
- Enjoy pairing with designers and user researchers, not just other engineers.
Why This Role MattersShopping online is broken. People have 47 tabs open, screenshots everywhere, links lost in texts. They're recreating the same searches daily, missing price drops, buying the wrong size.
We already capture that behavior and turn it into memory.
You’ll make that memory intelligent and build the agents that act on it.
You’ll help us fix shopping for millions of people—not with committees and roadmaps, but by building systems that know users deeply and quietly do work on their behalf.
Why Nora?Build Something NewWe’re not just optimizing conversion funnels. We’re creating a new layer for shopping: a personal memory and agent that answers to the user, not the retailer.
Meaningful EquityReal ownership in something that could change how people shop online. You’re early enough that your equity will matter.
Choose Your SetupRemote, in-person NYC, or hybrid. Full-time or contract. We care about impact, not hours logged.
The Interview ProcessSuper straightforward:
- Quick chat (30 min): Tell us about yourself, we’ll tell you about Nora and our data.
- Technical working session (60–90 min): We’ll walk through a simplified version of a real problem (e.g., memory search, alternatives, agents). You’ll talk through how you’d approach it. No LeetCode. No trick puzzles.
No whiteboard algorithm drills. Just real conversations about real work.
Compensation DetailsFull-time: $100K–$150K base salary + 0.25%–3.0% equity
Contract: Hourly or project-based, flexible depending on scope and location.
We're flexible and transparent — tell us what works for you.
Ready?Send us:
- Try the product and tell us why are you excited about Nora specifically?
- Your best example of an ML/LLM/search/recs system you shipped and what you learned.
- Links to anything you've built/written/created (optional but helpful).
Email: sid@checkwithnora.meor drop 30 mins on my calendar: calendly.com/sid-banothu/30min-hold
