Best Machine Learning Development Companies

BairesDev vs EPAM Systems: full comparison for 2026

Last updated: July 2026

Quick verdict

EPAM Systems (3.9/5) edges ahead of BairesDev (3.7/5) overall. EPAM Systems is the better choice for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration. BairesDev is the stronger option for companies needing rapid ML team scale-up using LATAM nearshore engineers in US time zones at competitive rates. The right choice depends on your project size, budget, and required tech stack.

BairesDev vs EPAM Systems: head-to-head summary

Criterion BairesDev EPAM Systems
Founded 2009 1993
HQ San Francisco, CA, USA Newtown, PA, USA
Team size 4,000+ 62,000+
Rating 3.7 / 5 3.9 / 5
Best for Companies needing rapid ML team scale-up using LATAM nearshore engineers in US time zones at competitive rates Large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration
Pricing model Dedicated team, T&M, Staff augmentation Dedicated team, T&M, Fixed project, Staff augmentation
Min. engagement $30K $50K
Primary tech stack Python, TensorFlow, PyTorch Python, TensorFlow, PyTorch
Industries served SaaS, fintech, healthcare, retail, media financial services, healthcare, retail, media, government

BairesDev vs EPAM Systems: overview

BairesDev

BairesDev is a technology solutions company founded in 2009 and headquartered in San Francisco, California. The company employs 4,000+ software engineers with expertise in over 100 technologies and has completed 1,200+ projects for enterprise clients. BairesDev's ML practice delivers via nearshore Latin American engineers working in US time zones, with a standardized hiring process the company claims selects the top 1% of LATAM developers (per company website; independently unverifiable). The firm charges $50–$99 per hour.

EPAM Systems

EPAM Systems is a global technology engineering company founded in 1993 and headquartered in Newtown, Pennsylvania. The company employs 62,000+ engineers across 50+ countries and is publicly traded on the NYSE. EPAM provides end-to-end AI development services from strategy and consulting to implementation and support, working with Fortune 500 clients across financial services, healthcare, retail, media, and government. EPAM is the largest firm in this review, with AI/ML capabilities delivered within a full-service technology engineering operation.

Services and capabilities: BairesDev vs EPAM Systems

Capability BairesDev EPAM Systems
Custom ML development
ML consulting
Deep learning
NLP
Computer vision
MLOps
Predictive analytics
Generative AI
Data engineering
Staff augmentation

Tech stack comparison: BairesDev vs EPAM Systems

Framework / platform BairesDev EPAM Systems
TensorFlow
PyTorch
Scikit-Learn N/A
LangChain N/A N/A
AWS SageMaker
Azure ML N/A
GCP Vertex AI N/A N/A
Kubernetes
Apache Spark
MLflow N/A

Pricing comparison: BairesDev vs EPAM Systems

Criterion BairesDev EPAM Systems
Minimum engagement $30K $50K
Engagement models Dedicated team, T&M, Staff augmentation Dedicated team, T&M, Fixed project, Staff augmentation
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: BairesDev vs EPAM Systems

Dimension BairesDev EPAM Systems
Best company size Startup to mid-market Startup to mid-market
Best industries SaaS, fintech, healthcare financial services, healthcare, retail
Best use cases Rapid ML engineering team scale-up for time-sensitive enterprise AI programme delivery, Staff augmentation for internal data science teams needing extra ML engineering capacity Global enterprise AI transformation programme requiring multi-country deployment and governance, Complex Fortune 500 ML programme integrating across dozens of legacy systems
Typical project type Dedicated team Dedicated team

BairesDev vs EPAM Systems: pros and cons

BairesDev
+ US time zone delivery from LATAM reduces the real-time collaboration gaps common with offshore Eastern European firms
+ Rapid team scale-up capability — 4,000+ engineer bench means fast ramp for urgent programmes
+ Competitive rates ($50–$99/hr) for the US time zone convenience offered
+ 1,200+ completed projects demonstrates execution consistency across verticals
+ Staff augmentation model suits organizations that need to extend internal ML teams quickly
- Top 1% talent claim is per company website only — independently unverifiable selection rigour
- Nearshore staffing model requires client-side ML programme management; BairesDev does not own outcomes
- Less specialist ML boutique depth for research-adjacent or novel model architecture challenges
EPAM Systems
+ 62,000+ engineers provides unmatched scale for simultaneous large-scale enterprise ML programmes
+ Publicly traded NYSE company with audited financials — maximum organizational stability and governance
+ Global delivery across 50+ countries enables ML delivery under local data sovereignty requirements
+ Full AI lifecycle from strategy through production MLOps within one organizational relationship
+ Fortune 500 client base validates enterprise-grade ML delivery at the highest complexity level
- Enterprise scale means ML projects go through larger organizational process — slower initiation than boutiques
- High minimum engagement ($50K) limits accessibility for SMBs or early-stage organizations
- Generalist technology engineering scope means ML specialist depth may be lower per individual than pure-play ML boutiques

Who should choose BairesDev?

BairesDev is the right choice for companies needing rapid ML team scale-up using LATAM nearshore engineers in US time zones at competitive rates.

4,000+ ML-capable LATAM engineers in US time zones with 1,200+ completed projects, enabling rapid scale-up for organizations that need to grow their ML capacity fast. Minimum engagement starts at $30K. Works best with clients in SaaS, fintech, healthcare, retail, media.

Who should choose EPAM Systems?

EPAM Systems is the right choice for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.

62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes. Minimum engagement starts at $50K. Works best with clients in financial services, healthcare, retail, media, government.

Decision matrix: BairesDev vs EPAM Systems

Your situation Recommended choice
You need full-ownership delivery on a defined project scope EPAM Systems
You need a large dedicated team for an ongoing programme BairesDev
Your budget is at the lower end BairesDev
You need specialist depth in a specific vertical BairesDev
You need staff augmentation or team extension BairesDev
You need consulting before committing to a build BairesDev

Use case fit: BairesDev vs EPAM Systems

Use case BairesDev fit EPAM Systems fit Winner
Rapid ML engineering team scale-up for time-sensitive enterprise AI programme delivery Strong Limited BairesDev
Staff augmentation for internal data science teams needing extra ML engineering capacity Strong Limited BairesDev
Global enterprise AI transformation programme requiring multi-country deployment and governance Limited Strong EPAM Systems
Complex Fortune 500 ML programme integrating across dozens of legacy systems Limited Strong EPAM Systems
Fixed-price build Limited Limited Both equally
Staff augmentation Strong Limited BairesDev

Verdict: BairesDev vs EPAM Systems

EPAM Systems (3.9/5) is the stronger overall choice for most Machine Learning Development projects. 62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes. It is best for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.

BairesDev (3.7/5) is the better choice when companies needing rapid ML team scale-up using LATAM nearshore engineers in US time zones at competitive rates. If your situation matches those criteria, BairesDev is a competitive option.

Related comparisons

BairesDev vs EPAM Systems FAQ

Is BairesDev better than EPAM Systems?

EPAM Systems (3.9/5) scores higher overall, but "better" depends on your use case. BairesDev is better for companies needing rapid ML team scale-up using LATAM nearshore engineers in US time zones at competitive rates. EPAM Systems is better for large enterprises requiring ML at Fortune 500 scale with global delivery capacity, stringent compliance requirements, and complex multi-system integration.

How do BairesDev and EPAM Systems differ in pricing?

BairesDev uses dedicated team, t&m, staff augmentation pricing with a minimum engagement of $30K. EPAM Systems uses dedicated team, t&m, fixed project, staff augmentation pricing with a minimum engagement of $50K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: BairesDev or EPAM Systems?

EPAM Systems is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.

What are the main differences between BairesDev and EPAM Systems?

BairesDev's primary differentiator is: 4,000+ ml-capable latam engineers in us time zones with 1,200+ completed projects, enabling rapid scale-up for organizations that need to grow their ml capacity fast. EPAM Systems's primary differentiator is: 62,000+ engineers across 50+ countries delivering ml inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise ai programmes. They also differ in team size (4,000+ vs 62,000+), minimum engagement ($30K vs $50K), and primary industries served (SaaS, fintech vs financial services, healthcare).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.