Founding Applied ML Engineer

David Joseph & Company; San Francisco (CA); On-site; USD 130,000 - 250,000; Full time

Job summary

David Joseph & Company in San Francisco is looking for a Founding Applied ML Engineer to build and optimize AI systems. As the first engineer, you'll play a crucial role in product engineering and work directly with clients, making high-stakes decisions.

The ideal candidate should have 3+ years of experience in applied ML, proficiency in Python and SQL, and a knack for building reliable AI models. This full-time position offers a compensation range of $130,000 to $250,000 along with equity opportunities.

Qualifications

• 3+ years applied ML or data science in production.
• Experience with ranking, attribution, forecasting, or product analytics.
• End-to-end ownership mindset and comfortable with ambiguity.

Responsibilities

• Build custom ML models to optimize brand performance.
• Design ranking and scoring systems for AI commerce.
• Develop data pipelines to generate actionable product intelligence.

Skills

Applied ML or data science in production

Full-stack Python and SQL

Ranking and attribution experience

Expert with AI tools like Claude or Cursor

Tools

Python

SQL

TypeScript

React

Job description

Founding Applied ML Engineer

San Francisco, CA · On-site · Full-time
Compensation: $130,000–$250,000 + 0%–4% equity

About the Company

An early-stage, venture-backed company building the optimization platform for agentic commerce — helping ecommerce and retail brands understand, improve, and monetize how their products show up across AI shopping agents. Growing 50% month over month, the team works directly with brands navigating the shift from traditional search to AI agent-driven discovery.

Founded 2025 · 1–10 people · Industry: AI Tools

The Role

Engineer number one. You are not joining an engineering team — you are helping build one. The role spans product engineering across the full stack plus applied ML judgment to build reliable AI systems: ranking systems, evals, attribution models, agents, and automation loops that customers actually trust. You will work directly with customers, own product and infrastructure decisions, and help shape what gets built and how as the market evolves in real time.

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
• 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 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

Why Join

• True founding scope — engineer #1, owning product and infrastructure decisions end to end
• Novel, product-grounded ML problems: ranking, evals, attribution, and agentic workflows
• Fast-growing team working directly with customers in a market evolving in real time

Details

• Location: San Francisco, CA
• Work policy: On-site (in-person)
• Compensation: $130,000–$250,000 + equity
• Visa sponsorship: None Available
• Employment type: Full-time