EPAM Systems
58,000-person global engineering firm ranked top-3 in Glassdoor's Best Tech & AI Companies 2026.
Founded 1993 | Newtown, PA, USA | 58,000+ employees | Last updated: July 2026
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What is EPAM Systems?
EPAM Systems is a global digital transformation services company founded in 1993 and headquartered in Newtown, Pennsylvania, with over 58,000 professionals worldwide. It was ranked among the top three tech and AI companies on Glassdoor's Best Places to Work 2026. EPAM's AI and ML practice covers custom ML development, data engineering, generative AI, MLOps, and staff augmentation, delivered across financial services, healthcare, media, SaaS, and logistics. EPAM is best suited to enterprises needing a large-scale delivery partner with the governance, compliance, and programme management infrastructure of a major consultancy at software engineering rates.
EPAM Systems was founded in 1993 and is headquartered in Newtown, PA, USA. The firm employs 58,000+ people and works primarily with clients in Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce sectors. Its primary differentiator is: Global scale with 58,000+ engineers and top-3 Glassdoor AI company ranking — rare ML delivery capacity for simultaneous large enterprise programmes.
EPAM Systems tech stack and services
PythonTensorFlowPyTorchAWSAzureGCPJava.NETKubernetesDatabricks
| Service area | Details |
|---|---|
| Enterprise-scale ML platform build requiring 50+ engineers across data engineering, ML, and MLOps tracks simultaneously | Available for Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce clients |
| Global digital transformation programmes embedding ML into enterprise software at multiple business units | Available for Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce clients |
| Staff augmentation with ML engineers on demand for large financial services or healthcare programmes | Available for Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce clients |
| Generative AI enterprise deployment with full compliance, security, and governance documentation | Available for Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce clients |
EPAM Systems use cases
Short answer: EPAM Systems is best suited for large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering.
| Use case | Industries | Approach |
|---|---|---|
| Enterprise-scale ML platform build requiring 50+ engineers across data engineering, ML, and MLOps tracks simultaneously | Financial Services, Healthcare | Python, TensorFlow |
| Global digital transformation programmes embedding ML into enterprise software at multiple business units | Financial Services, Healthcare | Python, TensorFlow |
| Staff augmentation with ML engineers on demand for large financial services or healthcare programmes | Financial Services, Healthcare | Python, TensorFlow |
| Generative AI enterprise deployment with full compliance, security, and governance documentation | Financial Services, Healthcare | Python, TensorFlow |
EPAM Systems pricing
Short answer: EPAM Systems uses a t&m, dedicated team pricing approach. Minimum engagement starts at $100K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
EPAM Systems does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
EPAM Systems pros and cons
| Advantages | Things to consider |
|---|---|
| +58,000+ engineers provide unmatched concurrent delivery capacity for large-scale enterprise ML programmes | -$100K minimum and large-firm overhead pricing makes EPAM less suitable for mid-market or startup buyers |
| +Glassdoor top-3 Best Tech & AI Company 2026 reflects high engineering talent quality and retention | -ML specialisation depth is diluted by the breadth of a 58,000-person general technology firm |
| +Full global delivery footprint enables follow-the-sun support and multi-geography data processing compliance | -Large firm bureaucracy and account management layers can slow decision-making on agile ML projects |
| +Strong programme management and governance infrastructure reduces enterprise delivery risk on complex projects | |
| +ML capability combined with broader digital transformation services reduces vendor proliferation for enterprise buyers |
EPAM Systems vs alternatives
How EPAM Systems compares to the other top Machine Learning agencies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tiger Analytics | Fortune 1000 enterprises needing production-grade ML across CPG,... | The largest pure-play ML and advanced analytics specialist with 5,000+ dedicated practitioners across six countries | 4.8 | Full comparison |
| Forte Group | Mid-market and enterprise teams that need ML treated... | Architecture-first ML delivery with AI embedded at every layer of the software stack, not added as an afterthought | 4.6 | Full comparison |
| Tensorway | Mid-market teams needing senior deep learning expertise in... | Boutique deep learning specialist with direct senior engineer access and AWS Premier Partner status, backed by Anadea's 25-year delivery track record | 4.5 | Full comparison |
| Fractal Analytics | Fortune 500 enterprises in CPG, financial services, or... | Deep Fortune 500 CPG and financial services track record with 5,000+ practitioners and a newly public balance sheet for long-term contracts | 4.4 | Full comparison |
| Quantiphi | Enterprises needing production ML on AWS with strong... | AWS Premier ML Consulting Partner with proprietary NeuralOps framework that accelerates time from training to production deployment | 4.3 | Full comparison |
| Sigmoid | Enterprises in CPG, retail, and BFSI that need... | Sequoia-backed firm combining data engineering and ML under one delivery team — eliminates the handoff friction that slows model deployment | 4.3 | Full comparison |
| DataForest | Growth-stage startups and mid-market teams needing production ML... | Clutch 5.0 / 27 reviews with project minimum from $8K — highest verified quality-to-price ratio at the accessible end of the market | 4.2 | Full comparison |
| InData Labs | E-commerce, healthcare, and fintech teams needing NLP, computer... | Top-10 Clutch-ranked cognitive computing and NLP specialist with competitive rates relative to Western boutiques of comparable review depth | 4.2 | Full comparison |
| RTS Labs | Mid-sized businesses in financial services or healthcare making... | Named top US ML consultant for mid-market businesses in 2026 — focused entry point with accessible minimums and healthcare/fintech domain depth | 4.2 | Full comparison |
| Grid Dynamics | Fortune 1000 enterprises in retail, CPG, or media... | Among the strongest retail and e-commerce AI practices globally, with verifiable ROI metrics from PayPal, eBay, and major US retailers | 4.1 | Full comparison |
| N-iX | Enterprises in manufacturing, industrial IoT, or retail needing... | Named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML | 4.1 | Full comparison |
| LeewayHertz | E-commerce, logistics, and financial services teams needing AI... | Forbes top-10 AI firm acquired by The Hackett Group — combining engineering delivery with enterprise AI strategic advisory capability | 4.1 | Full comparison |
| LatentView Analytics | Fortune 500 technology, CPG, and financial services firms... | Publicly listed analytics firm with 50+ Fortune 500 clients and deep CPG/tech marketing analytics capability including marketing mix modelling | 4.1 | Full comparison |
| Thoughtworks | Enterprises prioritising ML engineering rigour, responsible AI governance,... | AI-first consultancy with a structured engineering discipline — TDD, continuous deployment, and responsible AI built into ML delivery rather than grafted on afterwards | 4.0 | Full comparison |
| ScienceSoft | Manufacturing, healthcare, and oil & gas enterprises needing... | 35+ years of operation with ISO 9001 and ISO 27001 certifications — provides compliance-mandated vendor stability rare in the ML agency market | 4.0 | Full comparison |
| Oxagile | Media, healthcare, and manufacturing enterprises needing production computer... | 20-year heritage in video technology and media AI translates directly into best-in-class computer vision delivery for media, broadcast, and content platforms | 4.0 | Full comparison |
| Innowise | European enterprises in healthcare, financial services, or logistics... | ISO-certified ML delivery with 1,600+ engineers and GDPR-by-design data processing — strong fit for EU-regulated enterprise buyers | 4.0 | Full comparison |
| Miquido | Product companies in streaming, fintech, or healthtech needing... | Rare combination of ML, product design, and mobile engineering under one studio — ideal for building AI-powered consumer applications without managing multiple vendors | 4.0 | Full comparison |
| Itransition | Large enterprises seeking a stable 25-year vendor with... | Long-established 25-year vendor with 3,000+ engineers providing low-risk ML delivery for enterprises that value breadth and vendor stability over specialisation | 4.0 | Full comparison |
| Algoscale | Growth-stage and mid-market enterprises that need ML and... | Data-engineering-first ML delivery prevents the common failure where ML models are built on unreliable pipelines — end-to-end ownership from raw data to deployed model | 4.0 | Full comparison |
| Acropolium | European mid-market businesses in hospitality, logistics, or healthcare... | Munich-based EU-native ML boutique with specific delivery depth in hospitality, logistics, and healthcare — valuable for German-speaking and EU-regulated enterprises | 3.9 | Full comparison |
| DataArt | Financial services, media, and healthcare enterprises needing ML... | Software-engineering-first culture produces ML systems designed for 5-10 year production lifespans — maintainability and stability over speed-to-market | 3.9 | Full comparison |
| Addepto | Manufacturing, logistics, and retail SMEs needing a focused... | Focused vertical expertise in manufacturing predictive maintenance and retail AI at boutique scale — avoids the generalist overhead of larger firms for targeted use cases | 3.9 | Full comparison |
| BairesDev | US enterprises needing high-volume ML engineering hours with... | Latin American delivery provides full US timezone overlap and real-time collaboration at rates 30–50% below comparable US-onshore ML engineers | 3.9 | Full comparison |
| Intellias | Automotive, financial services, and retail enterprises needing ML... | Strongest automotive ML capability in this review — ADAS, connected vehicle data, and in-car AI built for a segment most ML agencies cannot credibly claim | 3.9 | Full comparison |
| DataRobot | Enterprises wanting rapid ML deployment via an enterprise... | Category-defining AutoML platform with $285M ARR — accelerates time-to-production ML without requiring a dedicated data science team | 3.9 | Full comparison |
| Binariks | Healthcare, SaaS, and fintech product teams needing accessible... | Accessible $15K minimum with healthcare and fintech domain ML experience — lower entry cost than larger European peers without sacrificing engineering quality | 3.8 | Full comparison |
| Softeq | Manufacturers, robotics companies, and IoT product builders needing... | Unique full-stack hardware-to-cloud capability — ML embedded into firmware and device systems without requiring a separate hardware engineering partner | 3.8 | Full comparison |
| Ekimetrics | CPG, retail, and media brands needing marketing mix... | Econometric and causal ML focus delivers explainable business-driver insights rather than black-box predictions — strongest for marketing analytics and brand measurement | 3.8 | Full comparison |
| BCG X | C-suite-sponsored AI transformation programmes where strategic consulting and... | BCG strategy consulting credibility combined with 3,000+ engineering practitioners — closes the strategy-to-build gap that typically requires two separate partners | 3.8 | Full comparison |
| Accenture AI | Global Fortune 500 enterprises needing enterprise-wide AI transformation... | 53,000+ dedicated AI practitioners — the only partner that can run simultaneous large-scale ML programmes across multiple continents without staffing constraints | 3.8 | Full comparison |
| Wipro AI | Large enterprises already in Wipro's managed services or... | Enterprise IT governance DNA applied to ML — model versioning, release governance, and audit trails built for highly regulated enterprise environments | 3.7 | Full comparison |
| Deloitte AI | Large enterprises needing AI delivery combined with regulatory... | Only Big Four firm with an AI Studio network and the ability to combine AI technical delivery with tax, audit, and regulatory advisory under one professional services relationship | 3.7 | Full comparison |
| IBM Consulting AI | Large enterprises with IBM infrastructure or WatsonX commitments... | WatsonX enterprise AI platform combined with IBM's 100+ year track record in regulated enterprise environments — strongest for clients already in the IBM ecosystem | 3.6 | Full comparison |
| Iguazio | Enterprises with existing ML models that need production-grade... | MLOps platform specialist with real-time AI serving and multi-cloud/edge deployment — best for operationalising models rather than building them | 3.5 | Full comparison |
EPAM Systems FAQ
What is EPAM Systems?
EPAM Systems is a global digital transformation services company founded in 1993 and headquartered in Newtown, Pennsylvania, with over 58,000 professionals worldwide. It was ranked among the top three tech and AI companies on Glassdoor's Best Places to Work 2026. EPAM's AI and ML practice covers custom ML development, data engineering, generative AI, MLOps, and staff augmentation, delivered across financial services, healthcare, media, SaaS, and logistics. EPAM is best suited to enterprises needing a large-scale delivery partner with the governance, compliance, and programme management infrastructure of a major consultancy at software engineering rates.
How much does EPAM Systems charge?
EPAM Systems uses t&m, dedicated team pricing. Minimum engagement starts at $100K. A discovery call is required to get project-specific quotes.
What tech stack does EPAM Systems use?
EPAM Systems works with Python, TensorFlow, PyTorch, AWS, Azure, GCP, Java, .NET, Kubernetes, Databricks. Primary industries served include Financial Services, Healthcare, Technology / SaaS, Media / Entertainment, Logistics, Retail / E-commerce.
Is EPAM Systems right for enterprise?
Large enterprises needing scale, global delivery coverage, and programme management infrastructure alongside ML engineering. 58,000+ team size. Key consideration: $100K minimum and large-firm overhead pricing makes EPAM less suitable for mid-market or startup buyers.
What are the best EPAM Systems alternatives?
The best alternatives to EPAM Systems depend on your use case. Top options are:
- Tiger Analytics: the largest pure-play ml and advanced analytics specialist with 5,000+ dedicated practitioners across six countries
- Forte Group: architecture-first ml delivery with ai embedded at every layer of the software stack, not added as an afterthought
- Tensorway: boutique deep learning specialist with direct senior engineer access and aws premier partner status, backed by anadea's 25-year delivery track record
Compare EPAM Systems with other Machine Learning agencies
EPAM Systems vs Tiger Analytics EPAM Systems vs Forte Group EPAM Systems vs Tensorway EPAM Systems vs Fractal Analytics EPAM Systems vs Quantiphi EPAM Systems vs Sigmoid EPAM Systems vs DataForest EPAM Systems vs InData Labs EPAM Systems vs RTS Labs EPAM Systems vs Grid Dynamics EPAM Systems vs N-iX EPAM Systems vs LeewayHertz EPAM Systems vs LatentView Analytics EPAM Systems vs Thoughtworks EPAM Systems vs ScienceSoft EPAM Systems vs Oxagile EPAM Systems vs Innowise EPAM Systems vs Miquido EPAM Systems vs Itransition EPAM Systems vs Algoscale EPAM Systems vs Acropolium EPAM Systems vs DataArt EPAM Systems vs Addepto EPAM Systems vs BairesDev EPAM Systems vs Intellias EPAM Systems vs DataRobot EPAM Systems vs Binariks EPAM Systems vs Softeq EPAM Systems vs Ekimetrics EPAM Systems vs BCG X EPAM Systems vs Accenture AI EPAM Systems vs Wipro AI EPAM Systems vs Deloitte AI EPAM Systems vs IBM Consulting AI EPAM Systems vs Iguazio
Last reviewed: July 2026. Verify all details directly with EPAM Systems before making a decision.