Executive Full Stack Machine Learning Engineer Jobs

Vendra is building the AI-native operating system for manufacturing procurement and supply chain. Our goal is simple: build platforms, both external and internal, that allow fewer people to accomplish dramatically more. Think about what Claude Code did for engineers. We are doing that for supply chain (and are well on our way).

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.

As a Full Stack Machine Learning Engineer, you will work across machine learning, frontend, backend, APIs, data systems, infrastructure, and core AI workflows that power our manufacturing marketplace and other platforms. You will collaborate directly with the founders, move fast, and work closely with customers building some of the most advanced hardware in the world.

We are already working with some of the most ambitious companies in aerospace, defense, robotics, and advanced manufacturing, including teams at Anduril, Mach Industries, Relativity Space, and more. Click here to see some of those names.

This is a role for builders who want to work on products that are used by the companies building the future of hardware. We are growing faster than anyone in this space, and the only way to keep up with the demand in front of us is to build faster, think bigger, and raise the bar on what one great engineer can ship.

• 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.

• 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.

• Help define product and technical vision
• Build new platforms and products that support our mission
• Develop a deep understanding of supply chain, procurement, and custom part manufacturing
• 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.

• You have 1+ years of experience building and shipping real products and experience with machine learning systems.
• We don't care about your degree; we care about the systems you've put into production. Tell us about those in the message you send over.
• 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. Confused? You should be. That’s what makes this fun.
• 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 DO NOT need experience in supply chain or hardware. You just need to be a really good engineer.
• 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.

Bonus: 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.

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

We plan, push, and ship features many times in a single day. You will not be stuck waiting weeks to see your work matter. At Vendra, the feedback loop is immediate: you build, customers use it, and the product gets better.

This role is a fit for someone who wants ownership, speed, ambiguity, and direct impact. You should be excited to work across the stack, talk to customers, make product decisions, and build systems that become the backbone of modern manufacturing procurement.

Vendra started from a simple realization: the hardest part of building hardware is not just managing suppliers. It is finding the right suppliers in the first place.

Before launching this version of Vendra one year ago, we spent six months building productivity tools for hardware teams working with manufacturers. But the deeper we got into the problem, the clearer it became that the real bottleneck was supplier discovery, quoting, and procurement.

So we pivoted. Within two weeks of the idea, we launched the first version of Vendra. Apple became our first customer, and we have been growing at lightspeed ever since.

Shan, CEO, designed camera systems at Microsoft and Apple for AR hardware, including HoloLens 2 and Vision Pro. He later led product development at Skydio for the X10 camera systems and NightSense modules, with thousands of drones and modules deployed around the world. He also holds multiple patents across product design and manufacturing design.

Anish, CTO, comes from a machine learning research and applied AI background across computer vision, NLP, logistics, and defense. After his stint in the research space, he became a Founding ML Engineer at Ship Angel, where he led development of autonomous logistics systems, and built satellite-data tracking systems for open-water intelligence at General Atomics.