Your mission

As a Machine Learning Engineer, you will play a pivotal role in building, optimizing, and maintaining the infrastructure for training and deploying machine learning models. Your focus will be on creating scalable, robust, and production-ready ML solutions while collaborating closely with our software engineers to bring ML models to life in real-world applications in the context of industrial procurement and supply chains.

• Infrastructure Development: Build and enhance infrastructure and data pipelines for modern machine learning applications, emphasizing modularity, scalability, and robustness.
• Great User Experience: Work closely with our customers and product development teams to achieve the best possible user experience and fine-tune the results.
• Workflow Optimization: Design and optimize APIs for machine learning development workflows integrating ML best practices at every step.
• Deployment and Monitoring: Deploy ML models into production environments and establish monitoring procedures to ensure model stability and performance.
• Shape the Stack: Stay updated on advancements in ML tools and concepts, and chose the right tools for the tasks.
• Sharing Best Practices: Share knowledge within the team to establish a common understanding across the whole organization.

Your profile

We’re looking for a talented ML / AI engineer to help us build the vision of making supply chains digital, efficient, and sustainable for our customers. Now you may wonder what frameworks, tools, and languages you need to master. We believe that problem-solving, creativity, and drive are more important than tools that can be picked up. However, the following references will give a guideline of what experiences we think might be helpful.

• Proven experience in building and deploying machine learning applications in real-world applications.
• Strong programming skills in languages such as Python, and familiarity with ML libraries, like TensorFlow, PyTorch, or sci-kit-learn.
• Experience with setting up a production-ready ML stack - modular and ready to scale.
• Solid foundations in software engineering best practices.
• You are up to date with the latest developments and advancements in the field of ML, e.g. LLMs, LMMs, etc..
• Proficiency in optimizing and troubleshooting production code.
• Taking tradeoff decisions and understanding to make sensible choices that fit the current phase of the company.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.

Tech Stack:

• Backend: Python, FastAPI, SQL Alchemy, Alembic, Pydantic, Pytest, …
• Frontend: TypeScript, NextJS, Zustand, Material UI, React Hook Form, …
• DB: PostgreSQL
• Data: Python, Prefect, Pandas, …
• Cloud: Azure
• Other: GitHub, GitHub Actions, Dependabot, Pre-commit, Mozilla SOPS, …

It is not expected to be completely familiar with each and every aspect of our tech stack.Other technologies that we enjoy discussing and encourage in the team:

• Backend: Golang, Rust
• Frontend: Vue / Nuxt, Svelte / Svelte Kit, Tailwind, Bun, tRPC, …
• Linux: Nix, Arch, Ubuntu, i3, …
• Other: LLMs, LMMs, NeoVim Configs, …