Role overview
Published via Mainder
We are looking for an Applied AI Engineer to join a high-impact team building real-world, production-grade AI solutions. This is an opportunity to work on complex and meaningful problems, where your work will directly influence business outcomes.
In this role, you will own solutions end-to-end — from working with raw data and building data pipelines to developing models and deploying them into production. It’s ideal for builders who enjoy working across the stack, combining data engineering and machine learning to bring ideas to life.
This is not a research-focused position or a traditional data engineering role. Instead, it’s designed for engineers who want to move fast, solve ambiguous problems, and create scalable solutions with a strong product mindset.
Design, build, and maintain end-to-end data and machine learning solutions
Develop and optimize data pipelines to ingest, process, and transform large datasets
Build and deploy machine learning models into production environments
Ensure reliability, scalability, and performance of data and ML systems
Work across batch and real-time data processing workflows
Collaborate with stakeholders to understand business problems and translate them into technical solutions
Monitor, evaluate, and iterate on models and pipelines based on performance and impact
Contribute to the overall architecture of data and ML platforms
Experience & Background
Experience as a Machine Learning Engineer, Applied Data Scientist, or Data Engineer with strong ML exposure
Proven track record of building and deploying production-grade solutions end-to-end
Experience working with both data pipelines and machine learning models
Background in fast-paced environments with high ownership (startups, consultancies, product teams)
Technical Skills
Strong Python skills
Experience with data processing and pipeline development (ETL, data modeling, transformations)
Experience with machine learning frameworks and model lifecycle
Experience deploying models (APIs, batch, or streaming systems)
Familiarity with cloud platforms and scalable data architectures
Understanding of both data engineering and ML concepts
Polymath-Oriented: Comfortable operating across engineering, design, business, and data science.
Curious Explorer: You lean into ambiguity, ask hard questions, and foster experimentation.
Outcome Owner: You prioritize business impact, own stakeholder relationships, and make pragmatic trade-offs.
Systems Thinker: You understand complex system interactions and anticipate downstream effects.
Precise Communicator: You translate seamlessly between technical and business contexts.
Problem Discoverer: You proactively uncover latent needs by embedding with users and shaping clear problem definitions.
People First culture.
Free access to streaming platforms.
Free access to Spotify premium.
GYM discount.
Legal and accountant advise.
Travel discount.
E-Learning discount.
Supermarket discount.
We are a global digital partner combining Strategy, Experience & Design, Engineering, and Managed Services to build digital solutions with real impact.
We work with modern technologies and ambitious teams to create scalable platforms that serve as the foundation for future growth, fostering a culture of collaboration, innovation, and technical excellence.