AI / ML / Data Science in IT — CIS and Europe market
AI / ML / Data Science is a family of roles: ML Engineer (production models and pipelines), Data Scientist (statistical analysis, A/B tests, ML models), AI Engineer (LLM, RAG, GenAI applications), MLOps (ML infrastructure), Computer Vision and NLP engineers. The core stack is Python, PyTorch, TensorFlow, scikit-learn, pandas, NumPy, Jupyter, MLflow, Kubeflow, HuggingFace Transformers, LangChain, OpenAI API, vector databases (Pinecone, Weaviate, Qdrant). According to Zorky CRM, the IT market across CIS and Europe currently has 1610 active AI/ML/DS openings with a median salary of $6300/mo. The most in-demand technologies — python, go, visio, rust, databricks. 89% of positions are remote. Active employers — Yandex, Sber, Tinkoff, VK, OZON, Wildberries, Kaspi, plus international AI teams at Anthropic, OpenAI, HuggingFace, Stability AI. Data refreshes daily.
AI / ML / Data Science is one of the core roles on IT teams. Over the last 3 months of observation across our 1000+ CIS and European sources this direction accounts for a significant slice of open IT jobs: 1 610 active positions as of the latest data refresh. Charts below render across the full available data window; text figures in the hero — the last quarter. On salary: median across the whole specialisation — $6 300/mo. Senior earns roughly 0.8× more than Junior — one of the most stable compensation gradients in IT. AI / ML / Data Science — one of the most remote-friendly IT specialisations: 89% of open positions are remote. There are 7 sub-specialisations inside this direction — a detailed breakdown of each follows below on this page.
Sub-specializations
AI/ML/DS breaks down into 7 sub-specialisations: ML Engineer (production models), AI/LLM Engineer (generative AI), MLOps (ML infrastructure), Computer Vision (images and video), NLP Engineer (text and language), Research Engineer (R&D), Data Scientist (statistics and A/B tests). Each niche has its own salary range — click a card for detail.
Click to see detailed analytics.
Demand trend
Over recent weeks the AI/ML direction has grown non-linearly — the explosive rise in demand since the releases of ChatGPT, Claude, Gemini in 2023–2025 continues in 2026. Fluctuations are normal; watch the overall trend.
How many new jobs appear each week.
Seniority distribution — trend
How the share of Junior/Middle/Senior/Lead in open jobs shifts week over week. A trend toward Senior usually signals a mature specialization where companies look for ready-made talent; the opposite — a rise in Junior — signals expansion and ground-up team building.
Share of each level in % of all jobs with a stated grade per week.
Salary by level
ML/AI engineer salary ladder: Junior $7796/mo, Middle $5040/mo, Senior $6405/mo, Lead $9325/mo. The strongest pay growth is between Middle and Senior (picking up production-ML and MLOps).
Median salary (USD/month) at each grade plus the jump vs the previous one.
Biggest salary jump — between Senior and Lead (+45.6%).
Salary distribution — trend
The median AI/ML salary on the market is $6300/mo. Most active jobs sit in the $4,500–9,000 band — the main mid-market segment. The $12K+ band is international AI teams (Anthropic, OpenAI, HuggingFace), Lead Research, and AI Engineer with LLM specialisation.
What share of jobs each price band holds week over week.
62% of jobs are in the $5–8K range (the core market). High-end $8K+ segment: 24% — usually US-remote or senior-international roles.
Hiring geography
The leader by AI/ML job count is 🇵🇱 Poland (321 positions), followed by the major IT hubs of CIS and Eastern Europe. Important: this is the distribution across our parsing sources, not a global market estimate.
Job distribution by country.
These numbers reflect the distribution across the sources we parse. Poland often looks dominant because of dense NoFluffJobs / JustJoin.it / Pracuj coverage — the Polish IT market is genuinely large, but in our sample its share is overweighted relative to the real volume of all IT jobs in the region. Same caveat for other top countries: this is «where our parsers look», not «the true size of the market».
Remote / Hybrid / Office — trend
89% of AI/ML jobs are full-remote; the rest are hybrid or office. Banks more often require hybrid because of compliance; international AI teams — full-remote is the standard.
How the share of each work format shifts week over week.
89% — remote. Specialisation is well-adapted to remote format.
Top in-demand technologies
The top ML/AI engineer stack in 2026 is Python, PyTorch, TensorFlow, scikit-learn, pandas. PyTorch dominates in research and AI startups; TensorFlow is a solid enterprise choice. HuggingFace Transformers and LangChain are must-have for AI Engineer.
Technology combinations
The most common technology pairs in AI/ML postings: Python+PyTorch, Python+TensorFlow, scikit-learn+pandas, HuggingFace+LangChain, MLflow+Airflow. If you are planning a learning roadmap, these combinations maximise market coverage.
Which pairs of technologies appear together most often in a single job.
Where we see these jobs
AI/ML jobs surface across most major sources: web parsers (HH, Habr Career, Djinni, DOU, NoFluffJobs, JustJoin.it) provide the bulk of the volume. Telegram channels add an exclusive stream — AI startups, GenAI/LLM positions, US-remote offers from Anthropic/OpenAI/HuggingFace.
AI / ML / Data Science vs other directions
AI/ML/DS is the highest-paid IT specialisation by median in 2026. Click any direction's bar to compare salaries, stack, and dynamics in detail.
Volume of open jobs across IT directions.
Latest jobs
Latest open AI/ML/DS jobs — the most recent 10 positions with adequate description quality. The full list is available in our CRM or via the "see all" link below.
Key takeaways
- Demand is real: 1 610 AI / ML / Data Science jobs opened over the last 3 months — not a theoretical market live positions with active hiring.
- Salary anchor: median $6 300/mo. Senior earns noticeably more than Junior — compensation gradient is substantial.
- Remote-friendly: 89% of positions are remote. You can work from any country in the region without relocating.
- Top technology: python with 360 jobs — if you're just starting in AI / ML / Data Science begin there.
If you plan to grow in AI / ML / Data Science or hire a team — these numbers give a hands-on slice of the market. To watch in real time or get alerts on new jobs matching specific parameters — that's our CRM product for recruitment agencies and in-house teams.
What we can offer
If you work with AI / ML / Data Science jobs or you're in this role yourself — we can close a specific task. Pick a format, leave a contact — we reply within 24 hours.
Frequently asked questions
The most common questions about the AI/ML/DS market: salaries by level, stack (PyTorch vs TensorFlow), ML Engineer vs Data Scientist vs AI Engineer, remote, where to start a career, Senior skills. Answers recompute automatically from current data.
How much does an ML engineer and Data Scientist earn in 2026?
The median ML engineer and Data Scientist salary across CIS and Europe is $6300/mo per Zorky CRM data from the last quarter (1610 active jobs). Pay depends on level and specialisation: Junior around $7796/mo, Middle $5040/mo, Senior $6405/mo, Lead $9325/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.
What does an ML/AI Junior, Middle, Senior, or Lead earn?
AI/ML/DS salary ladder (median USD/mo): Junior $7796, Middle $5040, Senior $6405, Lead $9325. 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.
How much do ML engineers earn in Moscow and St Petersburg?
In Moscow and St Petersburg ML engineers and Data Scientists earn close to the market median — $6300/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: 89% 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.
What stack is most often required of an ML engineer?
Top-5 technologies in AI/ML/DS postings: python, go, visio, rust, databricks. 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.
Who earns more — ML Engineer, Data Scientist, or AI Engineer?
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).
Can ML engineers work remotely?
Partially: 89% 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.
How is ML Engineer different from Data Scientist and Data Engineer?
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.
Which companies actively hire ML/AI engineers?
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.
Where to start to become an ML engineer in 2026?
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.
How many ML/AI jobs are open across CIS and Europe?
As of the latest data refresh, the Zorky CRM sample contains 1610 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 🇵🇱 Poland, 🇺🇸 USA, 🇷🇺 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.
Where do ML engineers earn more — in Russia or in Europe?
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.
What skills does a Senior ML engineer need in 2026?
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.
Similar specializations
Methodology
- Data period: in the hero and copy — the last 3 months. In the charts — the full available observation period (since parsers were launched, usually 2-3 months).
- Data is collected automatically from 1000+ sources — Telegram channels and job boards across CIS and Europe.
- Only live open jobs with a clear description are counted. Spam and duplicates are filtered out.
- Salaries are converted to USD/month at the current rate. Outlier values (lt;500 or gt;50K) are filtered out.
- Levels are normalized: Mid → Middle, Intern/Trainee → Junior, Principal/Staff/Expert → Lead.
- The first 2 weeks of data (parser ramp-up period) are not shown in the charts.
- Data is recomputed every day.
Authorship and citation
Analytics prepared by Zorky Research Team. Last updated: May 29, 2026 at 5:40 PM.
Data sources and methodology
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.
Zorky CRM (2026). AI / ML / Data Science in IT: CIS and Europe market. Accessed: 5/29/2026. URL: https://zorky.tech/en/research/ml