Applied Machine Learning Engineer

The opportunity

We are looking for an Applied Machine Learning Engineer to help design, evolve and test machine learning based applications. This role focuses on building, deploying and monitoring accurate, scalable, secure and reliable machine learning pipelines that will run on enterprise grade systems. Moreover, the key aspect of the work is experimental work for specific customer use cases and development purposes. Customer centric focus is essential. Fast troubleshooting, usability and accuracy are major performance KPI's for this role. We are looking for the self-motivated team player who wants to learn about all product components and contribute to improvement in all areas.

How you'll make a difference

• Practical implementation of ML models, algorithms and data transformations
• Code development
• Ensuring the high quality of the code by application of best practices and dev tools
• Analyzing business requirements and translating them into technical designs (reading and writing technical documentation);
• Running data science experiments for specific use cases and general improvements
• Sales support (demos for customers)
• Existing clients support (troubleshooting, automation scripts development, example preparation)
• AI agents development and configuration
• Writing unit tests
• CI/CD development and testing processes automation
• Code containerization
• Deployment and monitoring of ML pipelines to cloud
• Contribute to frontend and backend requirements
• Code reviews
• Documentation of your work
• Presentation results for stakeholders

• Degree in computer science, mathematics, or engineering; a PhD is considered a strong asset
• Good skills in Data Analytics and transformations (SQL, ETL, scripting, Power BI)
• Ability to work effectively in a team and contribute to shared goals, with strong attention to detail, accuracy, and a genuine interest in technology, along with a willingness to share knowledge
• You bring a strong problem-solving mindset and the persistence needed to deliver and document high-quality technical solutions
• Very good knowledge of Python and data science frameworks (e.g., TensorFlow, Pytorch, Pandas, scikit-learn, Numpy)
• Hands-on skills in modern AI, including large language models (LLMs) and AI agents
• Some experience applying numerical methods, stochastic process modeling, Bayesian statistics, Monte Carlo analysis, probabilistic modeling, nonlinear dynamical systems modeling, and statistical filtering
• Experience with GIT, Azure DevOps
• Good knowledge of Docker, Kubernetes, and cloud monitoring