Wildcard — Founding Applied ML Engineer

Type: Full-time | On-site | San Francisco, CA Compensation: $130,000–$250,000 + 0%–4% equity Hiring count: 1 Visa sponsorship: None Available Reports to: Founder (name / LinkedIn not provided on role page)

About Wildcard

Wildcard is the agentic commerce optimization platform for ecommerce and retail brands, helping them understand, improve, and monetize how their products show up across AI shopping agents. It is building mission control for agentic commerce — visibility, recommendations, execution, attribution, and automation in one platform — as the market shifts from traditional search to AI agent-driven discovery.

Founded: 2025 | Team size: 1–10 | Total funding: Seed Industry: AI Tools Website: wild-card.ai Office: San Francisco, CA

Why Candidates Should Join

• Engineer #1: True founding scope — not joining an engineering team, helping build one; owns product and infrastructure decisions end to end.
• Novel problem space: Ranking, evals, attribution, and agentic workflows for noisy AI commerce outputs — product-grounded ML, not pure research or pure analytics.
• Momentum: Growing 50% month over month, working directly with ecommerce and retail brands in a market that is evolving in real time.

Intake Call Summary

• No intake call transcript provided on the role page. To be added if/when an intake summary is supplied.

The Role

Engineer number one, spanning product engineering across the full stack plus applied ML judgment to build reliable AI systems — ranking, evals, attribution models, agents, and automation loops that customers trust. Works directly with customers and helps shape what gets built and how.

What You'll Be Doing

• Build custom ML models to classify prompts, predict opportunity, and prioritize what brands should optimize for
• Design and ship ranking, scoring, and evaluation systems for noisy AI commerce outputs
• Build incrementality and attribution systems that connect AI visibility to revenue outcomes for ecommerce brands
• Develop data pipelines to collect signals and turn them into usable product intelligence
• Move between modeling, analysis, implementation, and product decisions without waiting for direction
• Own core AI workflows and make them reliable with queues, retries, observability, evals, and workflow orchestration

Tech stack: Python, SQL; TypeScript, Express, React for full-stack / customer-facing work when needed

Requirements

• 3+ years applied ML or data science in production
• Full-stack Python and SQL, ship independently
• Ranking, attribution, forecasting, or product analytics experience a strong plus
• Expert with Claude, Cursor, or similar AI tools daily
• End-to-end ownership mindset, comfortable with ambiguity

Green Flags

• Founding engineer or early-stage startup background
• Shipped ML systems from research to production at real scale
• Ecommerce, marketplace, or search background
• Active outside work: personal projects, contributions, or published work in ML

Red Flags

• Pure academic or research background with no production deployment
• ML expertise but no full-stack or infrastructure depth
• No evidence of strong judgment with AI tools or uses them as a crutch to avoid thinking
• Prefers defined scope or traditional management structure

Role Details

Salary$130,000–$250,000Equity0%–4%On-site policyOn-site, San Francisco (in-person)Visa sponsorshipNone AvailableEmployment typeFull-timeLocationSan Francisco, CA

Screening Questions

• None provided on the role page. To be added if/when supplied.

Interview Process

Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Quick Call with Founder Stage 3 — Take-home Assignment Stage 4 — One to two-day work trial Stage 5 — Offer Extended Stage 6 — Candidate Hired — Candidate accepts and starts.