The international IT сompany Andersen invites a ML Engineer to join our dynamic and highly skilled professional team.
Andersen is a pre-IPO global software development company with over 18 years of experience delivering full-cycle IT services. We specialize in helping enterprises and fast-growing mid-sized businesses accelerate their digital transformation through modern, scalable, and secure software solutions.
Our company operates across a global network of 16+ development centers and offices, strategically located in North America, Western and Central Europe, the Middle East, and the Asia-Pacific region. With a strong team of over 3,700 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.
Must-haves:
- Experience as a ML Engineer or similar role for 3+ years.
- Strong programming skills in Python (with libraries such as scikit-learn, pandas, numpy, matplotlib).
- Solid understanding of machine learning algorithms (regression, classification, clustering, etc.).
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Hands-on experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with version control systems (e.g., Git).
- Experience with SQL and working with structured data.
- Understanding of ML model deployment (e.g., REST APIs with FastAPI/Flask, model packaging with Docker).
- Exposure to MLOps practices (e.g., pipeline automation, model monitoring, reproducibility).
- Excellent communication, critical thinking and problem-solving skills.
- Staying up to date with new ML techniques, frameworks, and tools.
- Level of English – from Intermediate+ and above.
Nice-to-have:
- Experience with cloud platforms (AWS, GCP, or Azure) and managed ML services (SageMaker, Vertex AI, etc.).
- Experience with MLFlow, DVC, Airflow, or other ML lifecycle tools.
- Familiarity with CI/CD for ML systems.
- Knowledge of big data tools (Spark, Hadoop, etc.).
- Understanding of data security and ethical AI considerations.
- Experience with either natural language processing (NLP) including LLM or computer vision. or agentic AI.
Reasons why this job would be interesting to you: