Full Stack ML Engineer

About the role

Vendra is building the AI-native operating system for manufacturing procurement and supply chain. You will be part of the core engineering team at Vendra. This is a high-ownership fullstack role where you will help shape everything from our architecture across multiple connected platforms to the product experiences our customers rely on every day.

Who You Are

• 1+ years of experience building and shipping real products and experience with machine learning systems.
• You understand software engineering principles. You also understand that they could be wrong at this stage. You know when to follow them and when to break past them.
• You are a true full stack machine learning builder. You can move from data and model development to React and TypeScript, backend APIs, databases, infrastructure, and AI workflows without needing everything perfectly defined.
• You use Claude Code, Cursor, or similar AI coding tools. You are not just “AI curious” and you are not just a pure “vibe coder.“ You have already changed the way you build because of these tools, and you are excited to push that even further.
• You are a US Person (Greencard works too)
• You are strong in at least one part of the stack and excited to work across the rest: machine learning, frontend, backend, APIs, data systems, infrastructure, and AI workflows
• You have experience with Python and have built with LLMs, traditional ML models, embeddings, retrieval, ranking, or agentic systems.
• You can take ambiguous product or customer problems and turn them into working software quickly
• You are comfortable working directly with founders, customers, and suppliers to understand what needs to be built
• You are excited by AI, automation, marketplaces, infrastructure, and the opportunity to transform a massive offline industry
• You want a high-ownership role where your work ships fast and matters immediately
• You are willing to learn fast. Requirements change, processes change. We iterate at lightspeed and prioritize on a case by case basis.

Requirements

You are a former founder, early startup engineer, machine learning engineer, applied scientist, or someone who has owned a product end to end before. We especially like people who know what it feels like to build from zero, talk to users, make tradeoffs, and keep shipping even when the path is messy.

What You Will Do

• Take ownership of a real production workflow across our marketplace, supplier portal, internal tools, or AI automation systems.
• Ship improvements used directly by customers, suppliers, or the Vendra team.
• Work directly with Shan, Anish, and the founding team to support our newest product lines.
• Use AI tools like Claude Code aggressively to move faster, prototype faster, and ship higher-quality software with fewer cycles wasted.
• Improve a production model, agent, data pipeline, or AI-powered workflow.

Within days

• Take ownership of a real production workflow across our marketplace, supplier portal, internal tools, or AI automation systems.
• Ship improvements used directly by customers, suppliers, or the Vendra team.
• Work directly with Shan, Anish, and the founding team to support our newest product lines.
• Use AI tools like Claude Code aggressively to move faster, prototype faster, and ship higher-quality software with fewer cycles wasted.
• Improve a production model, agent, data pipeline, or AI-powered workflow.

Within weeks

• Become responsible for one of our core platforms or machine learning systems.
• Suggest, plan, and execute product and engineering improvements.
• Help us design and build the next product in our stack.
• Improve backend systems, APIs, internal tools, and AI workflows that directly impact customers.
• Turn machine learning experiments into reliable production features.

Within months

• Help define product and technical vision.
• Build new platforms and products that support our mission.
• Work with us to automate more of the manufacturing procurement lifecycle from RFQ to supplier matching, quoting, ordering, tracking, and fulfillment using Agentic Workflows.
• Build feedback loops that improve our models using real customer, supplier, and operational data.

Our Tech Stack

• Frontend: React, Next.js, TypeScript
• Backend: Node.js, Python
• Machine Learning and AI: OpenAI models, Anthropic models, PyTorch, scikit-learn, embeddings, retrieval, ranking systems, custom fine-tuned models, and agentic workflows
• Infrastructure: AWS, Postgres, Redis, S3, MongoDB
• Data: Real-time quote intelligence, supplier availability, historical manufacturing performance, customer and supplier workflow data