> Markdown version of [/jobs/ext/1262386-senior-lead-ml-applied-scientist](https://www.wearedevelopers.com/jobs/ext/1262386-senior-lead-ml-applied-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior/Lead ML Applied Scientist - **Company:** Intuition Machines, Inc. - **Location:** Austria (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Code Review, Software Debugging, Distributed Systems, Machine Learning, Microsoft Office, Software Engineering, Machine Learning Operations - **Published:** July 14, 2026 - **Apply:** https://www.adzuna.at/details/5669680641 ## About the Role * 5+ years of professional experience in applied ML. * Proven experience with the entire modeling lifecycle: building, evaluating, and debugging large ML models. * Experience with large-scale categorical and structured data. * Expertise in real-time ML models, incremental learning, and online learning. * Strong understanding of ML fundamentals: bias-variance tradeoffs, loss functions, evaluation metrics, etc. * Bachelor's degree in a technical field (or equivalent practical experience). * Thoughtful, self-directed individual who is comfortable making technical decisions independently. Nice to Have: * Strong grasp of the math required for ML (linear algebra, probability theory, statistics, matrix calculus). * Software engineering/development experience with large-scale distributed systems. * Ability to collaborate with ML engineers to integrate your work into our infrastructure, including automating observability, deployment, quality, and security. ## Description Österreich Befristet SCHNELLBEWERBUNGHOME-OFFICE Intuition Machines uses AI/ML to build enterprise security products. We apply our research to systems that serve hundreds of millions of people, with a team distributed around the world. You are probably familiar with our best-known product, the hCaptcha security suite. Our approach is simple: low overhead, small teams, and rapid iteration. As an ML Applied Scientist, you will design, implement, and scale machine learning systems that power our products. You'll work across teams to translate business goals into technical specifications, ensuring our models perform efficiently under real-world constraints. This role combines research, engineering, and mentorship in a fast-paced production environment. Using AI: Coding agents are indisputably useful tools. We provide access to the top 3 models, and were early adopters of evals-first development flows. Familiarity with coding using agents is part of all interviews. However, reliability and correctness are critical for us. You will need to read and understand every line of code with your name on it, and it will be reviewed by both people and machines. What you will do: * Build ML models that can scale to millions of requests per second while maintaining performance. * Translate business requirements into technical specifications. * Develop ML models that satisfy memory and compute constraints, evaluate them properly, and debug effectively. * Provide technical mentorship to other ML research engineers. * Iterate quickly, with a focus on shipping early and often, ensuring that new products or features can be deployed to millions of users. * Write clearly structured, maintainable, well-documented, and tested code, including unit, integration, and end-to-end tests. * Participate in code reviews and architecture & design sessions. Stay updated on recent technological developments and assess their applicability. * Provide technical input to the research roadmap. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Machine Learning in ML.NET](https://www.wearedevelopers.com/videos/272-machine-learning-in-ml-net) - [Are Code Reviews Worth It? Insights from 16 Years of Review Data](https://www.wearedevelopers.com/videos/1135-are-code-reviews-worth-it-insights-from-16-years-of-review-data) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [Intelligent Automation using Machine Learning](https://www.wearedevelopers.com/videos/157-intelligent-automation-using-machine-learning) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)