Principal Machine Learning Engineer (f/m/x) at exmox

Hamburg, , Germany -

Full Time

Start Date

Immediate

Expiry Date

15 Oct, 26

Salary

0.0

Posted On

17 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, TensorFlow, PyTorch, SQL, Databricks, MLOps, Applied Statistics, Data Engineering, LLM APIs, ETL/ELT, Model Deployment

Industry

Advertising Services

Description

Your Mission This is a company built for growth. When you join exmox, you're stepping into a high-velocity environment where data is not just analyzed but turned into systems that directly drive business performance. You will operate at the intersection of data, engineering, and product, solving real-world problems in a space that demands both speed and precision. We build high-performing consumer products in one of the most competitive industries: mobile gaming. As part of a company on a path of hyper-growth, you will help shape how machine learning becomes a core driver of our innovation, from smarter decision-making to scalable, production-ready intelligence across our platform. If you're looking for a role where you only experiment or stay in research, this isn't it. As a Principal Machine Learning Engineer (f/m/x) at exmox, you’ll lay the foundation for how ML is built, deployed, and scaled across the company, turning insights into systems and models into measurable impact. You’ll own the full ML lifecycle end to end, from first idea through production and continuous improvement, working closely with Data Science, Data Engineering, and Product. AI is core to how we operate, not just what we build: we use AI tools daily to work smarter, cut out repetitive work, and spend our time where it actually moves the needle. If that mindset speaks to you, you’ll fit right in. If this sounds like your kind of challenge, we want to hear from you. What you’ll own Machine learning systems & impact You design, build, and deploy machine learning models that solve real business problems. You focus on production-ready systems that directly influence product performance, user behavior, and revenue, not just offline experiments. End-to-end ML lifecycle You take ownership from experimentation to deployment and beyond. You validate models, ship them into production, monitor their performance, and continuously iterate to improve outcomes in dynamic environments. Collaboration across data & engineering You work closely with Data Scientists and Analysts to translate insights, metrics, and hypotheses into scalable ML solutions. At the same time, you partner with Data Engineers to ensure robust data pipelines, feature availability, and reliable model deployment. ML infrastructure & foundations As one of the first ML engineers, you help define how ML is done at exmox. You establish best practices, tooling, and architecture for model development, deployment, versioning, and monitoring, building the foundation for future scale. Translating ambiguity into systems You take loosely defined problems and turn them into structured ML solutions. You make trade-offs, define approaches, and bring clarity where none exists yet. What You Bring Strong applied ML experience You bring 7+ years of solid experience in machine learning, applied statistics, or data science, with a clear focus on real-world, production use cases, not just theoretical work. Technical depth & programming skills You are highly proficient in Python and experienced with modern ML libraries such as TensorFlow or PyTorch. You write clean, maintainable, and production-ready code. You actively use AI tools in particular Claude as part of your development workflow, and know how to leverage LLM APIs to accelerate prototyping, research, and production feature development. Data & infrastructure understanding You are comfortable working with data pipelines and infrastructure, including SQL, data warehouses, ETL/ELT workflows, and Databricks. You understand how data flows power reliable ML systems. Production mindset You have hands-on experience with deploying, versioning, and monitoring models in real-world environments. You think beyond training toward scalability, reliability, and long-term performance. Communication & translation skills You can translate business and analytical questions into ML problems and clearly explain ML concepts to non-technical stakeholders, aligning teams around practical solutions. Builder mentality You thrive in ambiguity and fast-moving environments. You create structure where none exists, make pragmatic decisions, and take ownership of outcomes from start to finish. What You Can Expect Ambitious people, real ownership. You’ll work with driven, entrepreneurial people who care deeply about what they deliver, challenge each other openly, and own outcomes together. We’re playing at the top, but we’re not done. Our apps rank in the top 5 of their categories. We’re determined to push further, compete harder, and earn the number one spot. You own your own growth. Growth doesn’t happen by accident. At exmox, learning is built into the work - through responsibility, feedback, and real challenges. Perks that help you focus on what matters. Transport subsidy, learning budget, wellness and gym, workation, bi-weekly team lunches, and more. The perks are great - but the real reason people join and stay is the challenge, the people, and the drive to win together. Please note: this is not a remote only position, we offer you a flexible hybrid model here in Hamburg, Germany - working from home on Mondays & Fridays, coming to the office on Tuesday, Wednesday & Thursday! About us At exmox, we are building the next European tech challenger in the user acquisition space. We operate a scalable user acquisition platform that enables partners to grow efficiently and at scale. In a highly competitive global market, our ambition is clear: to build a category-leading company through strong execution, continuous improvement, and a relentless focus on performance. This is not a company built for comfort. We are building for growth, impact, and long-term success.

Responsibilities

Design, build, and deploy production-ready machine learning systems that drive business performance and revenue. Establish the company's ML infrastructure, best practices, and end-to-end lifecycles from experimentation to monitoring.