Top 10 Companies Hiring AI Engineers in Ukraine in 2026
By Irene Holden
Last Updated: April 26th 2026
Too Long; Didn't Read
SoftServe and EPAM Ukraine lead the 2026 AI hiring landscape, with SoftServe's Generative AI Lab offering senior salaries up to 350,000 UAH per month and EPAM committing to hire 750-800 junior engineers for accessible entry. Grammarly and Samsung R&D provide top compensation for NLP and research specialists, while MacPaw and Preply attract engineers focused on privacy and marketplace AI. The best choice depends on your specialization - whether you want to build agentic systems, scale platforms, or research on-device models.
There's a moment in every Kyiv workshop when a craftsman stops scanning the wall of chisels and reaches for exactly one. The others are excellent tools - sharp, well-balanced, expensive. But only this one will fit the groove he's about to cut. Stand in front of a 2026 job board and you face the same choice: SoftServe offering 350,000 UAH/month, Grammarly dangling equity, EPAM opening its junior pipelines. The wall of opportunity is overwhelming.
A bad hire costs a company 30% of annual salary. A bad fit costs you months of your career. Every listicle pretends the ranking is the answer - it's not. According to Glassdoor's 2026 machine learning engineer salary data for Ukraine, the junior range spans 65,000-120,000 UAH/month while lead architects command 330,000-600,000+ UAH/month. The market pays for specificity, not generic rank.
These ten companies aren't competing with each other. Grammarly needs NLP researchers who love ambiguity. Samsung needs PhDs who love C++. MacPaw needs privacy-obsessed Swift developers. The "best" company is the one whose technical groove matches your career chisel. Alcor's 2026 AI engineer salary report shows that product companies like Grammarly and Preply offer equity and top-tier compensation while service firms like EPAM provide structured pipelines and breadth - each serves a different career arc.
Stop asking "Which company is number one?" Start asking "What kind of AI engineer am I becoming?" The 2026 market rewards engineers who know exactly what they are. Be the tool that fits, not the one that's ranked.
Table of Contents
- The Right Fit for Your AI Career
- MacPaw
- Preply
- Luxoft
- Ciklum
- N-iX
- Samsung R&D Institute Ukraine
- GlobalLogic
- Grammarly
- EPAM Ukraine
- SoftServe
- Choosing Your Groove
- Frequently Asked Questions
- If you want to launch an AI career in Ukraine's tech hubs, this complete guide is essential reading.
MacPaw
If you've ever felt uneasy about sending user data to a cloud API just to get a prediction, MacPaw is your workshop. This Kyiv-based product company builds intelligence that lives entirely on your device - no data leaves your Mac or iPhone. When CleanMyMac predicts which files you'll never touch again, or when photo curation organizes your library without uploading a single image, that's MacPaw's on-device AI at work. Privacy is a hard technical constraint here, not a marketing checkbox.
The tech stack reflects this philosophy: Python for training, Swift for on-device inference, CoreML, TensorFlow Lite, and MLFlow. You'll work in a specialized AI/ML lab with distinct roles for ML Engineers, Research Engineers, and macOS Engineers - a tightly focused unit that values innovation over scale. Their on-device photo curation, intelligent malware detection, and user behavior forecasting define the frontier of privacy-preserving AI. According to SalaryExpert's 2026 ML engineer compensation data for Ukraine, mid-level pay ranges 160,000-230,000 UAH/month, senior 270,000-380,000 UAH/month, and lead roles reach 450,000+ UAH/month.
The interview process tests your comfort with constraints: coding rounds, a take-home specifically focused on on-device ML optimization (running a model on a laptop battery), and a deep technical interview probing mobile inference optimization. As noted by ERI Economic Research Institute's salary benchmarks, MacPaw's compensation is competitive with larger service companies, but the real draw is the work itself. If you read CoreML documentation for fun, argue about on-device latency budgets, and have Swift in your blood, you've found your groove.
Preply
Preply operates one of Ukraine's most data-intense marketplaces, matching thousands of tutors with students in real-time. Their AI doesn't just recommend the right teacher - it optimizes pricing dynamically, predicts student churn, and powers adaptive learning tools that adjust to individual progress. The data streams flowing through Kafka into SageMaker training pipelines create an engineering challenge as demanding as the ML itself. This is product-led AI at scale, where every model directly impacts business metrics. The centralized Data & AI organization feeds intelligence into every product corner: Data Scientists build models while ML Engineers deploy and scale them. The tech stack runs deep with Python, PyTorch, Kafka, AWS SageMaker, Snowflake, and DBT. Mid-level compensation ranges 180,000-250,000 UAH/month, senior roles reach 300,000-420,000 UAH/month, and lead positions exceed 500,000+ UAH/month including stock options. According to Glassdoor's AI engineer salary data for Kyiv, Preply's total compensation places it among the top-paying product companies in the country. Who thrives here? Engineers who love data pipelines as much as model architectures. Product thinkers who can explain why a tutor recommendation failed in business terms, not just technical ones. The interview process reinforces this: live coding, deep ML fundamentals (know your bias-variance tradeoff cold), a product case study on retention, and a values round assessing cultural fit. Preply's 90% internal adoption rate of AI coding tools signals a company that builds for scale and uses its own products - every engineer here thinks about AI as both builder and user.Luxoft
Luxoft is where AI meets the physical world at speed. Their Ukrainian teams work on Advanced Driver Assistance Systems (ADAS) that must distinguish a pedestrian from a lamppost at 80 km/h using Lidar and camera sensor data. On the FinTech side, the same rigorous approach applies to algorithmic trading signals and risk models. This is domain-specific AI that demands you understand both the model and the machinery it controls. The work rewards engineers who find real-time constraints intellectually satisfying rather than frustrating. The team structure follows industry-vertical lines: Automotive, FinTech, and other domains operate as separate pods. Computer Vision Engineers, MLOps specialists, and classic AI researchers each own distinct responsibilities. The tech stack pairs Python and PyTorch with ROS (Robot Operating System), Kubernetes, and AWS/Azure. According to Glassdoor's 2026 machine learning engineer salary data for Ukraine, mid-level compensation runs 140,000-210,000 UAH/month, senior roles reach 230,000-340,000 UAH/month, and lead positions command 380,000+ UAH/month. The interview process reflects the domain's specificity:- C++ and Python coding rounds testing algorithmic thinking and systems knowledge
- Industry-specific ML problems such as calibrating a computer vision model for variable lighting conditions
- Soft skills assessment ensuring you can collaborate with domain experts who don't speak "ML"
Ciklum
Ciklum operates as a practical AI consultancy that guides clients from "we should do something with AI" to production systems generating measurable ROI. Their centralized Center of Excellence defines best practices, then embeds engineers directly into client delivery teams. This structure means you'll build breadth fast: a personalization engine for a retailer one quarter, a document classifier for a regulated bank the next. According to DesignRush's 2026 ranking of top AI companies in Ukraine, Ciklum's Product Discovery culture is a key differentiator - teams spend as much time understanding business constraints as writing code.
The tech stack spans Python, TensorFlow, Kubernetes, Airflow, Hugging Face, and Azure OpenAI Service. Compensation reflects the breadth of work: junior roles start at 65,000-90,000 UAH/month, mid-level reaches 130,000-180,000 UAH/month, senior positions command 210,000-300,000 UAH/month, and lead engineers earn 330,000+ UAH/month. The interview process mirrors real consulting: a technical interview covering ML fundamentals, a take-home task with ambiguous requirements, and a system design round testing your reasoning about data pipelines and deployment trade-offs.
As one Ciklum team lead explained in their overview of practical AI implementation, the company's value lies in helping clients separate "AI hype" from "AI ROI." This is the place for engineers who enjoy the consulting mindset - talking to stakeholders, translating vague requirements into specifications, and solving problems across industries. Jack-of-all-trades thrive here because the variety itself becomes your specialty.
N-iX
N-iX doesn't build models in isolation - they build complete data-to-AI pipelines for organizations that have data but no models, or models but no deployment infrastructure. Their dedicated Data Unit embeds ML Engineers directly into client squads with clearly delineated roles: Data Engineers own the pipelines, ML Engineers own the models, and MLOps engineers own the deployment infrastructure. The result is production-grade systems designed to run reliably at 3 AM, not Jupyter notebooks.
The tech stack reflects this pipeline-first philosophy: Python, Apache Spark, MLFlow, Snowflake, AWS SageMaker, and Azure ML. Client work spans fraud detection for global fintech companies, demand forecasting for retail supply chains, and anomaly detection in logistics networks. According to Built In's listing for a Lead AI/ML Engineer at N-iX, the company is actively expanding its AI talent across Ukraine. Junior roles start at 70,000-95,000 UAH/month, mid-level reaches 135,000-185,000 UAH/month, senior engineers earn 220,000-300,000 UAH/month, and lead positions command 340,000+ UAH/month.
The interview process tests your pipeline maturity: a practical coding round where you implement a model end-to-end, a SQL and data engineering challenge (can you query a messy dataset?), and a client-specific technical interview simulating stakeholder collaboration. N-iX is one of the fastest-growing Ukrainian tech brands by headcount, and their emphasis on infrastructure means you'll never be stuck building prototypes that can't scale.
Samsung R&D Institute Ukraine
While other companies test whether you can ship code, Samsung R&D Institute Ukraine tests whether you understand the mathematics behind it. This is the academic frontier of Ukrainian AI - a centralized R&D lab where PhDs are common, and the culture rewards publication alongside product impact. You're surrounded by people who think in first principles, many from their strong pipelines with Kyiv Polytechnic (KPI) and Kharkiv National University. The primary role is "Research Engineer," and you'll be expected to contribute to both open research and internal product roadmaps. The projects match this intellectual rigor. Computer vision that runs entirely on your phone - no cloud, no latency. NLP powering Bixby's continued evolution. Security-preserving ML that processes sensitive data without ever leaving the device. The tech stack pairs Python, C++, PyTorch, and JAX with custom on-device ML frameworks for mobile and IoT. Mid-level compensation reaches 160,000-240,000 UAH/month, senior engineers earn 280,000-420,000 UAH/month, and lead roles command 500,000+ UAH/month. The interview process is the most demanding on this list:- High-difficulty algorithm rounds at LeetCode-hard territory
- Deep ML theory testing your understanding of transformer architectures and attention mechanisms
- Paper review sessions where you discuss a recent publication in depth
GlobalLogic
GlobalLogic engineers don't just train models - they train models that control physical hardware in real-time. As a Hitachi Group company, their Ukrainian teams work at the interface of online and physical technologies: smart power grids that optimize energy distribution with ML, driver safety systems using computer vision for in-cabin monitoring, and automated testing frameworks applying AI to software quality assurance. This is embedded intelligence that demands you think in memory constraints and clock cycles, not just GPU availability.
The tech stack reflects this dual nature: C/C++ for embedded AI, Python, Google Cloud Vertex AI, and NVIDIA NeMo, with OpenCLAW for agent orchestration. Teams organize around physical systems - you're never just training a model, you're training one that must run deterministically on custom hardware. Junior roles start at 70,000-100,000 UAH/month, mid-level reaches 130,000-190,000 UAH/month, senior engineers earn 220,000-310,000 UAH/month, and lead positions command 350,000+ UAH/month. The interview process mirrors the hybrid nature with both Python and C/C++ coding rounds, then system design for high-load, low-latency inference systems.
GlobalLogic was named IT Industry Leader in the 2026 Opendatabot Index, reflecting its dominant position in Ukraine's tech ecosystem. According to the IT Ukraine Association's coverage of the award, this recognition is based on headcount, revenue growth, and industry impact. For AI engineers, the distinctive advantage is the embedded ML expertise - GlobalLogic runs transformers on microcontrollers, not just cloud GPUs. If you've been waiting for ML to catch up to your C++ skill set, this is where your groove gets carved.
Grammarly
Grammarly operates as Ukraine's most recognized AI research powerhouse, where the line between academic research and production engineering barely exists. Their embedded AI squads within specific product domains - Grammarly Business, Editor, and others - attract the country's top NLP specialists who dream in attention patterns. The company owns massive proprietary datasets: billions of writing corrections that no competitor can replicate, creating an insurmountable data moat for their context-aware generative writing tools, real-time tone adjustment, and multi-modal feedback loops that analyze user editing patterns.
The tech stack reflects this research intensity: Python, PyTorch, Ray for distributed training, Kubernetes, and custom MLOps for large-scale LLM fine-tuning. Mid-level compensation reaches 220,000-280,000 UAH/month, senior roles command 350,000-480,000 UAH/month, and lead architects earn 550,000+ UAH/month - frequently including equity. According to Levels.fyi's ML/AI salary data for Ukraine, Grammarly's total compensation at senior levels exceeds most other Ukrainian employers by a significant margin.
The interview process is the most rigorous product-company gauntlet in Ukraine: coding rounds, deep ML theory specifically on Transformers and attention mechanisms, a product-thinking case study (design a feature helping non-native speakers write more confidently), and a team-fit round. Their research output rivals academic institutions, supported by active partnerships with Taras Shevchenko National University. If you can explain the difference between decoder-only and encoder-decoder architectures without looking it up, and you want your research to touch 30 million daily active users, Grammarly's groove was carved for you.
EPAM Ukraine
EPAM operates at a scale that transforms the Ukrainian AI landscape itself. Their "Rule of Three" pods - Product Manager, Subject Matter Expert, and GenAI Builder - create a structured approach where junior engineers learn from hundreds of contributors and codebases that touch millions of users. The tech stack spans Python, Java for AI integration, TensorFlow, Airflow, and their proprietary EPAM AI Run CLI tool, giving you the infrastructure of a global company with the mentorship density of a focused lab. This is the most accessible entry point for an AI career in Ukraine, with 750-800 junior hires planned in 2026 alone.
Compensation reflects this structured pipeline: junior roles start at 75,000-110,000 UAH/month, mid-level reaches 140,000-200,000 UAH/month, senior engineers earn 240,000-330,000 UAH/month, and lead positions command 380,000+ UAH/month. The interview process tests your ability to think beyond code: standard coding rounds, a deep dive into GenAI architecture like RAG and agentic patterns, and behavioral rounds focused on "outcome-based delivery" - can you explain how you'd measure success before you start writing? EPAM built the AI portal for Ukraine's State Statistics Service, a public sector digital transformation processing terabytes of government data, alongside autonomous QA agents and retail systems handling the full "discovery-to-mediation" lifecycle.
EPAM is also a key partner in Ukraine's National LLM project, a government initiative to build a sovereign large language model scheduled for beta in 2026. According to their guide on building GenAI dream teams, the company treats public sector AI as a strategic priority, not a consulting engagement. Engineers who want structured mentorship, enterprise scale, and the chance to build platforms that thousands of other developers will use will find their groove carved in EPAM's workshops.
SoftServe
Choosing Your Groove
The 2026 market in Ukraine rewards one thing above all else: specificity. Grammarly needs researchers fluent in attention mechanisms. SoftServe builds engineers who create agentic systems that act on the world. MacPaw requires developers who optimize ML for a laptop battery's wattage. Samsung demands PhDs who derive first principles from scratch. A chisel doesn't care if it's ranked number one. It cares if it fits the groove you are cutting. Pick the groove first.
The compensation data tells the same story. According to Levels.fyi's ML/AI salary data for Ukraine, the spread between a generalist senior engineer and a specialized AI lead exceeds 200,000 UAH/month in many cases. The market pays a premium for engineers who know exactly what they are. As the 2026 IT recruitment forecast from dev.ua's market analysis notes, hiring has shifted away from "cheap hands" toward specialists who can own a domain end-to-end. The generalist safety net is gone; the specialist's workshop is thriving.
Stop asking "Which company is number one?" Start asking "What kind of AI engineer am I becoming?" The answer determines whether you join Grammarly's research lab, SoftServe's agent foundry, MacPaw's on-device crucible, or Samsung's academic workshop. Be the tool that fits exactly into the groove you intend to carve. The 2026 market rewards the engineer who knows their shape - and nothing else matters.
Frequently Asked Questions
Which company pays the highest salary for AI engineers in Ukraine in 2026?
Grammarly tops the list with senior salaries up to 480,000 UAH/month plus equity, followed by SoftServe at 350,000+ UAH/month. But 'highest' depends on role - Samsung R&D and Preply also offer competitive packages, and total compensation at lead levels can exceed 500,000 UAH/month including stock options.
I'm a junior AI engineer with no experience - where should I apply?
EPAM Ukraine is your best bet - they've committed to hiring 750-800 junior engineers in 2026, with salaries starting at 75,000 UAH/month and a structured mentorship program. Ciklum and N-iX also offer junior roles with clear growth paths.
Which companies focus on research vs. production AI work?
Samsung R&D and Grammarly lean heavily toward research and publication, with PhD-heavy cultures and paper review interviews. SoftServe and GlobalLogic emphasize production AI that interacts with physical systems, while MacPaw and Preply balance product-focused engineering with practical ML deployment.
Do any of these companies offer remote work or equity?
Yes - Grammarly, Preply, and MacPaw include equity or stock options, especially at senior and lead levels. Most companies offer flexible remote or hybrid arrangements, especially after the pandemic, though roles at Samsung R&D and Luxoft may require more on-site presence due to hardware labs.
How do the interview processes differ across these companies?
Samsung R&D has the hardest interviews with LeetCode-hard algorithms and deep ML theory, while Ciklum gives a take-home task with ambiguous requirements. SoftServe focuses on MLOps system design, and Grammarly adds a product-thinking case study. EPAM emphasizes 'outcome-based delivery' and behavioral fit.
Read our article on the best women in tech communities in Ukraine.
Learn how to evaluate AI salary offers in Ukraine.
See the best tech apprenticeships in Ukraine 2026 with data from EPAM, SoftServe, Grammarly, and more.
If you're in Kyiv, Lviv, or Kharkiv, don't miss the best free tech training at local libraries in 2026.
Creative States and LIFT99 are highlighted in our ranking of the top coworking spaces for tech in Ukraine.
Irene Holden
Operations Manager
Former Microsoft Education and Learning Futures Group team member, Irene now oversees instructors at Nucamp while writing about everything tech - from careers to coding bootcamps.