ML Engineer Trainee

Andersen is an international IT company and a recognized leader in outsourcing development. 90% of our projects are delivered for global clients across banking and fintech, as well as healthcare, e-commerce, logistics, and telecom — industries where technology drives real impact. We are growing fast, and we create opportunities for talented people to grow with us.

Andersen is launching a large-scale traineeship campaign in Baku with unique traineeship conditions for those who want to start a career in Machine Learning.

From day one, you will join a fully paid traineeship that accelerates your growth and prepares you for real commercial projects — and once you step into a project, you will move to a competitive, market-level salary that reflects your new role as a Machine Learning engineer.

About the Traineeship

The Machine Learning Engineer Traineeship at Andersen is more than learning — it is a fast and structured entry into the IT industry and real commercial projects.

This program is designed for candidates who are ready to develop intensively and become ML Engineers in a short period of time.

What we offer:

• 3 months: from your first day in the Lab to your first day on a commercial project;
• Full-time — 5 days a week, 8 hours a day: an intensive format with mandatory office attendance that truly accelerates your growth;
• Bring your own laptop: your device + our training = a specialist ready for real tasks;
• Focus on learning: this traineeship is primarily about gaining knowledge and skills. Successful graduates receive a Junior 1 offer

Who We Are Looking For

The one who understands the value of machine learning technologies and wants to build a career in Machine Learning engineering.

Requirements:

• Intermediate or higher level of English (verbal communication);
• understanding of probability, statistics and hypothesis testing fundamentals;
• data preprocessing and EDA skills (missing values, outliers, feature engineering);
• knowledge of classical ML algorithms (linear/logistic regression, trees, ensemble methods, clustering);
• model evaluation techniques (accuracy, precision, recall, ROC-AUC, regression metrics, cross-validation);
• experience with scikit-learn and basic ML pipelines;
• understanding of feature selection, scaling and dimensionality reduction methods;
• basic knowledge of NLP concepts and text representations (TF-IDF, embeddings);
• understanding of ML system lifecycle (training, evaluation, deployment basics).

Will Be a Plus:

• participation in relevant competitions, olympiads, or machine learning conferences;

• experience with gradient boosting frameworks (XGBoost, LightGBM, CatBoost);

• knowledge of model interpretability techniques (SHAP, LIME);

• familiarity with deep learning basics (NN, CNN, transformers);

• experience with ML tooling (MLflow, DVC, FastAPI, Docker);

• understanding of model monitoring and data drift concepts.

What’s cool about us:

• Experienced mentors and regular technical checkpoints — you always understand your current level and next steps;

• Personal curator — supports you throughout the journey and helps you stay on track even in challenging moments;

• Modern ML stack — work with cutting-edge technologies and gain experience with real enterprise-level projects and gain experience with real enterprise-level projects;

• Clear grading system and fast growth — you always know what is required to move forward;

• Corporate English — because most of our projects are international;

• Continuous learning culture — not a perk, but a core part of our environment. We provide access to our internal educational platform with courses and learning materials in one place.

Why Apply Now

We are launching a large-scale intake in Baku with enhanced traineeship conditions available until August 31, 2026 only. This is a limited-time opportunity to start your Machine Learning career on highly competitive terms, including a fully paid traineeship and a fast track to a commercial role.

Apply now and take your first step with Andersen!

Challenges are part of the journey — real opportunities are the reward.