Melrose Founding Applied AI Engineer West Hollywood, CA · San Francisco, CA · Full time Company website

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Melrose is building the AI connectivity layer for the global supply chain. AI is becoming the new operating system for work, but global logistics still runs on emails, PDFs, spreadsheets, portals, phone calls, and EDI. That gap is why moving goods is still harder than it should be. We’re building the first AI CSR to support global logistics teams and change the way goods move around the world. Melrose automates the quote-to-delivery workflow, mapping real world atoms to digital bits. We’re an operator-led team of ex-Sequoia backed founders with experience from Flexport, Uber, and Amazon. We’re backed by leading Silicon Valley investors who also back Rippling, Ramp, SpaceX, and Polymarket

About Melrose

Melrose is building the AI connectivity layer for the global supply chain.

AI is becoming the new operating system for work, but global logistics still runs on emails, PDFs, spreadsheets, portals, phone calls, and EDI. That gap is why moving goods is still harder than it should be.

We’re building the first AI CSR to support global logistics teams and change the way goods move around the world. Melrose automates the quote-to-delivery workflow, mapping real world atoms to digital bits.

We’re an operator-led team of ex-Sequoia backed founders with experience from Flexport, Uber, and Amazon. We’re backed by leading Silicon Valley investors who also back Rippling, Ramp, SpaceX, and Polymarket.

About the role

As Melrose’s founding Applied AI Engineer, you will build the intelligence layer behind our products. You will work on the systems that ingest messy operational data, reason across workflows, and automate work that today lives in inboxes, spreadsheets, portals, and customer service teams.

You will work directly with Dhaman (CEO) and our technical executive team. You will have tight feedback loops with customers, direct exposure to production problems, and real influence over how our AI systems are designed, evaluated, and shipped.

What you’ll do

• Build AI product systems that automate real logistics workflows across quote, order entry, milestone tracking, exception handling, and customer communication
• Design and ship reliable LLM-powered workflows using the right mix of models, retrieval, structured outputs, orchestration, and software engineering fundamentals
• Work with messy real-world inputs including emails, PDFs, spreadsheets, EDI, APIs, and portal data to turn unstructured operations into usable product
• Prototype quickly, then harden what works into production systems with strong observability, evals, fallback logic, and human-in-the-loop workflows where needed
• Partner closely with engineering, product, and leadership to identify the highest leverage automation opportunities and turn them into shipped product
• Build internal tooling and evaluation systems to measure quality, speed, accuracy, edge cases, and business impact across AI workflows
• Improve model performance through prompt design, workflow design, retrieval quality, context management, tool use, and systematic error analysis
• Own the full loop from problem definition to implementation to iteration, including talking to users, reviewing failures, and improving product behavior over time
• Help shape our technical architecture and engineering culture as an early builder on the team

What you’ll need

• Strong software engineering fundamentals. You can build production systems, not just demos
• Experience building with LLMs in real products, including prompting, tool use, structured extraction, agents, evals, and failure handling
• Comfort working across ambiguity. You can take a messy business problem and turn it into a scoped technical system
• Strong product instinct. You care whether something is actually useful, not just technically interesting
• Curiosity and speed. You like getting close to the workflow, understanding what users are actually doing, and iterating fast
• A high bar for quality and reliability. You understand that applied AI in operations needs tight feedback loops and careful design
• Clear communication. You can explain tradeoffs simply and work cross-functionally with technical and non-technical teammates
• High ownership and urgency. You do not wait for perfect specs

Nice to haves

• Experience building AI products in operations-heavy environments
• Exposure to logistics, supply chain, freight forwarding, trucking, or 3PL workflows
• Experience with document extraction, workflow automation, or human-in-the-loop systems
• Familiarity with evaluation frameworks, observability tooling, and production monitoring for LLM systems
• Experience at a high-growth startup or as an early engineer on a small team
• Comfort working across backend, data, and product surfaces as needed

What success looks like

• AI workflows that ship quickly and hold up in production
• Meaningful reduction in manual operational work for customers
• Systems that improve every week based on evals, user feedback, and failure analysis
• High trust from customers and teammates because the product is useful, fast, and reliable
• A growing foundation of repeatable AI primitives that accelerate new products and integrations

Benefits (U.S.-based full-time employees)

• Competitive salary plus meaningful equity
• 100% Medical, dental, and vision coverage
• Flexible PTO
• Budget for travel to customer meetings and industry events
• Home office support as needed
• Direct mentorship from the CEO and technical executive team