Вакансия ML Engineer

Skills

• Python
• scikit-learn
• Pandas
• NumPy
• matplotlib
• TensorFlow
• PyTorch
• Keras
• Git
• SQL
• Rest API
• FastAPI
• Flask
• Docker
• AWS
• GCP
• Azure
• AWS SageMaker
• Vertex AI
• MLflow
• DVC
• AirFlow
• CI/CD
• Apache Spark
• Hadoop
• NLP
• LLM

Описание вакансии

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 15+ 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 3,500 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 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.

Desired skills

• 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.