Best AI Staff Augmentation Companies

BairesDev vs ScienceSoft: full comparison for 2026

Quick verdict

BairesDev (4.3/5) edges ahead of ScienceSoft (3.7/5) overall. BairesDev is the better choice for U.S. companies needing several AI engineers on matching hours. ScienceSoft is the stronger option for regulated companies wanting a documented hiring process. The right choice depends on your project size, budget, and required tech stack.

BairesDev vs ScienceSoft: head-to-head summary

Criterion BairesDev ScienceSoft
Founded 2009 1989
HQ San Francisco, California, USA McKinney, Texas, USA
Team size 4,000+ 750+
Rating 4.3 / 5 3.7 / 5
Primary differentiator A large salaried Latin American bench that works U.S. time zones Publishes its staff augmentation timeline and process
Pricing model Monthly per-engineer rates for staff augmentation; dedicated teams; project pricing; rates on request Hourly or monthly rates shared with CVs; time and materials
Min. engagement Not published Not published
Primary tech stack Python, TensorFlow, PyTorch Python, Azure ML, AWS
Industries served Software & SaaS, Financial services, Healthcare & life sciences, Media, Retail & e-commerce Healthcare & life sciences, Financial services, Manufacturing, Retail & e-commerce

BairesDev vs ScienceSoft: overview

BairesDev

BairesDev was founded in Buenos Aires in 2009 and now lists its headquarters in San Francisco. The company says it employs more than 4,000 professionals working remotely from over 50 countries, most of them in Latin America. It offers staff augmentation, dedicated teams and full software outsourcing, with an AI and data science practice inside the wider engineering group. BairesDev hires engineers onto its own payroll, so clients deal with one vendor contract rather than individual freelancers.

ScienceSoft

ScienceSoft dates its IT work to 1989 and is headquartered in McKinney, Texas. It says its staff augmentation pool covers more than 750 professionals, including data scientists with long industry experience, and it publishes a fast hiring sequence: CVs with rates within a day, interviews in two to four days and starts in one to two weeks (per company website; independently unverifiable). AI is one of many service areas alongside its long-standing healthcare and finance work.

Services and capabilities: BairesDev vs ScienceSoft

Capability BairesDev ScienceSoft
LLM / GenAI engineers ✓ ✗
MLOps & deployment ✗ ✗
Computer vision ✗ ✗
Data engineering ✓ ✓
AI agent development ✗ ✗
Fractional / part-time experts ✗ ✗
Risk-free trial period ✗ ✗
Nearshore time-zone overlap ✓ ✗

Tech stack comparison: BairesDev vs ScienceSoft

Framework / platform BairesDev ScienceSoft
PyTorch ✓ N/A
TensorFlow ✓ N/A
LangChain N/A N/A
Hugging Face N/A N/A
OpenAI ✓ N/A
AWS ✓ ✓
Azure ✓ ✓
Databricks ✓ N/A
MLflow N/A N/A
Kubernetes N/A N/A

Pricing comparison: BairesDev vs ScienceSoft

Criterion BairesDev ScienceSoft
Minimum engagement Not published Not published
Engagement models Full-time dedicated engineers, Dedicated team, Managed delivery Full-time dedicated engineers, Dedicated team
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: BairesDev vs ScienceSoft

Dimension BairesDev ScienceSoft
Best company size Startup to mid-market Startup to mid-market
Best industries Software & SaaS, Financial services, Healthcare & life sciences Healthcare & life sciences, Financial services, Manufacturing
Best use cases Adding three ML engineers to a U.S. product team on Eastern time, Staffing data engineering and model serving together for a new AI feature Adding a data scientist to a healthcare analytics team, Staffing BI and ML roles for a manufacturer
Typical project type Full-time dedicated engineers Full-time dedicated engineers

BairesDev vs ScienceSoft: pros and cons

BairesDev
+ Full working-day overlap with U.S. teams makes pairing and live reviews easy
+ Can fill AI, data and the surrounding web roles from one contract
+ Engineers are salaried employees, so replacement is the vendor's problem
- AI is one practice among many, so screening depth for ML research roles varies
- Pricing is quoted per engagement and is reported to sit above smaller nearshore rivals
- Heavy marketing makes it hard to separate its AI claims from its general engineering pitch
ScienceSoft
+ Shares rates together with candidate CVs
+ Long history in healthcare and finance
+ Clear published hiring timeline
- AI is a small part of a very wide catalog
- Fewer GenAI specialists than AI-focused firms
- Speed figures come from its own marketing

Who should choose BairesDev?

A typical fit: adding three ML engineers to a U.S. product team on Eastern time.

A large salaried Latin American bench that works U.S. time zones. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Financial services, Healthcare & life sciences, Media, Retail & e-commerce.

Who should choose ScienceSoft?

A typical fit: adding a data scientist to a healthcare analytics team.

Publishes its staff augmentation timeline and process. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare & life sciences, Financial services, Manufacturing, Retail & e-commerce.

Decision matrix: BairesDev vs ScienceSoft

Your situation Recommended choice
You need a dedicated team for a long programme Both; BairesDev rates higher overall
You want the supplier to own delivery as well as staffing BairesDev
You need one expert part-time Neither lists part-time experts; ask about reduced hours
You want to test an engineer before signing for months Neither publishes a trial; ask for a short first term
Your budget is at the lower end Compare: BairesDev (Not published) vs ScienceSoft (Not published)
You need overlap with U.S. working hours BairesDev
You need specialist depth in a specific vertical BairesDev

Use case fit: BairesDev vs ScienceSoft

Use case BairesDev fit ScienceSoft fit Winner
Adding three ML engineers to a U.S. product team on Eastern time Strong Strong Both equally
Staffing data engineering and model serving together for a new AI feature Strong Strong Both equally
Adding a data scientist to a healthcare analytics team Strong Strong Both equally
Staffing BI and ML roles for a manufacturer Strong Strong Both equally

Verdict: BairesDev vs ScienceSoft

BairesDev (4.3/5) is the stronger overall choice for most AI Staff Augmentation projects. A large salaried Latin American bench that works U.S. time zones.

ScienceSoft (3.7/5) is worth a look if you need staffing BI and ML roles for a manufacturer. If your situation matches that, ScienceSoft is a competitive option.

Related comparisons

BairesDev vs ScienceSoft FAQ

Is BairesDev better than ScienceSoft?

BairesDev (4.3/5) scores higher overall, but "better" depends on your use case. BairesDev's strongest advantage: full working-day overlap with U.S. teams makes pairing and live reviews easy. ScienceSoft's strongest advantage: shares rates together with candidate CVs.

How do BairesDev and ScienceSoft differ in pricing?

BairesDev uses monthly per-engineer rates for staff augmentation; dedicated teams; project pricing; rates on request pricing. ScienceSoft uses hourly or monthly rates shared with cvs; time and materials pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: BairesDev or ScienceSoft?

BairesDev 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 ScienceSoft?

BairesDev's primary differentiator is: a large salaried Latin American bench that works U.S. time zones. ScienceSoft's primary differentiator is: publishes its staff augmentation timeline and process. They also differ in team size (4,000+ vs 750+), minimum engagement (Not published vs Not published), and primary industries served (Software & SaaS, Financial services vs Healthcare & life sciences, Financial services).

Verify all details directly with each company before making a decision.