ML Engineer

We are looking for an ML Engineer in the EU to join an international software development and outsourcing company and work on a project focused on designing, training, and deploying scalable machine learning models, building ML pipelines, and supporting production-ready AI solutions in an international tech environment.

Andersen is a pre-IPO software development company providing a full cycle of services. For over 19 years, we have been helping enterprises and middle-sized firms worldwide transform their businesses by creating effective digital solutions using innovative technologies.

Our company operates across a global network of 16 development centers, strategically located in North America, Western and Central Europe, the Middle East, and the Asia-Pacific region. With a strong team of over 3,500 highly skilled professionals, we combine deep domain expertise and advanced technical capabilities to consistently deliver exceptional results for our clients.

Responsibilities:

• Designing, training, and evaluating machine learning models (supervised, unsupervised, NLP, etc.).

• Building scalable data and ML pipelines using modern tools.

• Collaborating with subject matter experts and analysts to prepare training datasets.

• Deploying models for production (batch or real-time inference).

• Monitoring and maintaining model performance and data quality.

• Optimizing models for performance, interpretability, and cost.

• Documenting ML workflows and ensuring reproducibility.

Requirements:

• Experience as a Machine Learning Engineer or in a similar role for 2+ years.

• Proficiency in Python, including hands-on experience with libraries such as scikit-learn, pandas, NumPy, and matplotlib.

• Strong understanding of core ML concepts – regression, classification, clustering, model validation, and performance metrics.

• Practical experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.

• Proven experience building, training, and deploying ML models using AWS SageMaker.

• Familiarity with AWS Bedrock for working with foundation and generative models (e.g., fine-tuning and orchestration of LLMs).

• Hands-on experience with data preprocessing, feature engineering, and model evaluation.

• Knowledge of SQL and experience working with structured and semi-structured datasets.

• Understanding of ML model deployment (e.g., REST APIs with FastAPI or Flask; model packaging and containerization with Docker).

• Exposure to MLOps practices – pipeline automation, model versioning, monitoring, and reproducibility.

• Familiarity with version control systems (e.g., Git).

• Strong analytical thinking, communication, and problem-solving skills.

• Willingness to stay current with emerging ML techniques, frameworks, and cloud AI tools.

• Level of English – from Upper-Intermediate and above.

• Level of German – from Intermediate+ and above.

• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc.

• The opportunity to change the project and/or develop expertise in an interesting business domain.

• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.

• Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.

• The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.

• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.

• Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).

• Certification compensation (AWS, PMP, etc).

• Referral program.

• English courses.

• Private health insurance and compensation for sports activities.