AI / ML / Data Science in IT — CIS and Europe market

The median ML engineer and Data Scientist salary across CIS and Europe is $7880/mo per Zorky CRM data from the last quarter (2408 active jobs). Pay depends on level and specialisation: Junior around $5778/mo, Middle $4043/mo, Senior $8135/mo, Lead $8570/mo. AI/ML is in the top-3 highest-paid IT directions thanks to specialist scarcity and the growth of the GenAI market. AI Engineer (LLM, GenAI) pays the most — Senior $7,000–12,000/mo in 2026 on local market. Computer Vision and Research Engineer — $6,500–10,000/mo. In international AI teams (Anthropic, OpenAI, HuggingFace) — $10,000–25,000/mo for Senior. Salaries are normalised to USD.

AI/ML/DS salary ladder (median USD/mo): Junior $5778, Middle $4043, Senior $8135, Lead $8570. Junior openings are few — the market expects the level of a technical-university graduate with Kaggle pet projects or production experience from an internship. The biggest jump is between Junior and Middle (picking up production-ML: MLOps, model monitoring, A/B tests). Lead usually moves into Head of ML or Research Lead. The most practical path to Junior: Python + scikit-learn + one of PyTorch/TensorFlow + 2–3 serious pet projects (not the Titanic dataset). 2026 trend: companies are more actively hiring backend developers with basic ML than pure Data Scientists without production experience.

In Moscow and St Petersburg ML engineers and Data Scientists earn close to the market median — $7880/mo. Moscow traditionally pays more thanks to Yandex (search, recommendations, AI Lab), Sber and Tinkoff (anti-fraud, scoring), VK (recommendations), OZON and Wildberries (e-commerce ML). St Petersburg is close thanks to Avito and game studios. Remote is partial: 41% of jobs are full-remote, but banks often require hybrid because of compliance. In Poland (Warsaw, Krakow) Senior ML — $5,500–10,000/mo. Berlin and Prague — €5,500–9,500. Almaty is a growing hub at $3,000–6,500. International AI startups (Anthropic, OpenAI, HuggingFace) — $10,000–25,000+ for Senior regardless of country of residence.

Top-5 technologies in AI/ML/DS postings: python, cloud, llm, sql, pytorch. Required baseline skills: Python (advanced), statistics and linear algebra, classical ML via scikit-learn. Deep Learning — one of PyTorch (dominant in research) or TensorFlow (more production-friendly). Data work — pandas, NumPy, Jupyter. SQL is mandatory. For AI Engineer (LLM, GenAI): HuggingFace Transformers, LangChain, OpenAI API, Anthropic API, vector databases (Pinecone, Weaviate, Qdrant). For MLOps: MLflow, Kubeflow, Airflow, Docker, Kubernetes. A cloud (AWS SageMaker, GCP Vertex AI) is required at Senior.

In 2026 AI Engineer (LLM, GenAI, RAG) is the highest-paid niche: Senior $7,000–12,000/mo on local market, $15,000–25,000+ in international AI teams. Demand is growing explosively since the releases of ChatGPT, Claude, and Gemini. ML Engineer (production models, recommendations, anti-fraud) — Senior $6,000–10,000/mo, steady demand in fintech and e-commerce. Data Scientist (statistics, A/B tests, classical ML) — $5,000–8,500/mo, slightly lower because of larger supply. MLOps Engineer — $6,500–10,000/mo, specialisation on infrastructure. Research Engineer (R&D, papers at NeurIPS/ICML) — a high ceiling in international labs (Anthropic, OpenAI, DeepMind).

Partially: 41% of ML/AI jobs are full-remote. Banks and fintech (Sber, Tinkoff, Alfa) often require hybrid because of compliance on work with PII and financial data. Marketplaces (OZON, Wildberries, Avito) — more often hybrid. International AI teams (Anthropic, OpenAI, HuggingFace, Stability AI, Cohere) — almost always remote-friendly or hybrid with an office in SF/NYC/London. AI startups — full-remote is the standard. Remote pay is markedly higher thanks to the global candidate pool and the premium GenAI segment. Few Junior remote openings exist — production training requires mentorship and access to compute resources.

ML Engineer — production focus: designing, training, deploying, and monitoring ML models. Stack: Python, PyTorch/TensorFlow, MLflow, Docker, Kubernetes. Close to a Backend engineer with an ML specialisation. Data Scientist — research focus: statistics, A/B tests, hypotheses, dashboards, sometimes ML models. Stack: Python, scikit-learn, Jupyter, pandas, SQL, sometimes R. Data Engineer — data infrastructure: ETL pipelines, warehouses, streams. Stack: Spark, Airflow, Kafka, ClickHouse. By pay: ML Engineer and AI Engineer usually pay above Data Scientist (more technical); Data Engineer is close to ML. Career flow: Backend → ML Engineer, Analyst → Data Scientist, Data Engineer ↔ ML Engineer.

The top AI/ML/DS employers across CIS and Europe: Yandex, Sber, Tinkoff — large product, fintech, and search companies with dozens of AI/ML positions. Yandex (search, Market, recommendations, AI Lab), Sber and Tinkoff (anti-fraud, scoring, credit scoring), VK (recommendations, ads, virtual assistants), OZON and Wildberries (recommendations, demand forecasting), Avito (duplicate listings, antifraud), Kaspi.kz (fintech ML). On the international side — Anthropic, OpenAI, HuggingFace, Cohere, Stability AI, Mistral, DeepMind actively hire Senior level on remote with pay multiples of the local market. AI startups from YC and a16z — a premium segment for Senior and Research.

The optimal path: master Python (advanced), statistics and linear algebra at university level, SQL, pandas + NumPy for data work. Then scikit-learn (classical ML: regression, classification, clustering) and one of PyTorch (recommended for research) or TensorFlow. Pet projects that look good: an end-to-end ML project with production deployment (not just a Jupyter notebook), 1–2 Kaggle competitions with silver medal or higher, contributions to open-source ML libraries. At Middle add MLOps (MLflow, Airflow), one cloud (AWS SageMaker or GCP Vertex AI). At Senior — a deep understanding of distributed training, model serving, A/B tests in production.

As of the latest data refresh, the Zorky CRM sample contains 2408 active open AI/ML/DS positions across CIS and Eastern Europe. These are postings published in the last 90 days — companies actually hiring. Geography is distributed; the leaders are 🇺🇸 USA, 🇬🇧 United Kingdom, 🇷🇺 Russia. Data is collected from 1000+ sources: Telegram channels (an exclusive stream for AI startups and niche LLM positions), specialised job sites (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it, Pracuj.pl), and career pages of fintech and AI teams. Seasonality: ML/AI demand grows non-linearly — an explosive rise since 2023 after ChatGPT, continuing in 2026 with releases of Claude, Gemini, Llama.

In absolute USD, Europe is consistently higher: in Poland (Warsaw, Krakow) Senior ML — $5,500–10,000/mo; in Germany (Berlin) €5,500–9,500/mo; in Czechia (Prague) €5,000–8,500. In Russia — Moscow Senior $4,500–8,500/mo, regions $3,000–6,500/mo. The main driver of the gap is contract currency and company type. International AI teams (Anthropic, OpenAI, HuggingFace, Cohere, DeepMind) and US startups pay multiples higher: Senior ML Engineer $15,000–25,000/mo, AI Engineer / LLM specialist $20,000–40,000+/mo (including equity). Local Russian companies on rouble contracts have closed the gap to the Polish market over 2 years. Georgia and Armenia attract many remote relocants on international pay.

A Senior ML/AI engineer owns the full production-ML stack. Baseline: Python (advanced), statistics and linear algebra, SQL, pandas, NumPy. Deep Learning: PyTorch or TensorFlow (one deeply). Production: MLflow or Weights & Biases (experiments), Airflow or Kubeflow (pipelines), one cloud ML (SageMaker, Vertex AI). For AI Engineer/LLM: HuggingFace Transformers, LangChain or LlamaIndex, OpenAI API, Anthropic API, vector databases (Pinecone, Weaviate, Qdrant), fine-tuning (LoRA, QLoRA), prompt engineering. Architectural patterns: model serving (Triton, TorchServe), A/B tests in production, distributed training, model versioning.

Data is collected automatically from 1000+ sources — Telegram job channels and job boards across CIS and Eastern Europe (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it, Pracuj.pl and others). Parsing runs 24/7, duplicates are filtered by description and URL, salary outliers are stripped. Detailed methodology — on the "How it works" page.