Top AI Engineer Staffing Companies

Proxify vs N-iX: full comparison for 2026

Quick verdict

Proxify (4.4/5) edges ahead of N-iX (3.9/5) overall. Proxify is the better choice for european companies that want a vetted ML or data engineer on European working hours. N-iX is the stronger option for large companies that want ML and data engineers from an established Central European supplier. The right choice depends on your project size, budget, and required tech stack.

Proxify vs N-iX: head-to-head summary

Criterion Proxify N-iX
Founded 2018 2002
HQ Stockholm, Sweden Valletta, Malta (delivery mainly in Ukraine and Poland)
Team size 5,000+ network members 2,000+
Rating 4.4 / 5 3.9 / 5
Primary differentiator Senior-engineer interviews with live coding after an automated skills test Scale and two decades of history in Central European delivery
Pricing model Hourly rate per developer billed monthly; full-time or part-time; rates on request Monthly per engineer or managed team; rates on request
Min. engagement Not published Not published
Primary tech stack Python, PyTorch, TensorFlow Python, Spark, Databricks
Industries served SaaS, Fintech, E-commerce, Media, Healthcare Financial services, Manufacturing, Retail, Telecom, Healthcare

Proxify vs N-iX: overview

Proxify

Proxify was founded in Stockholm in 2018 (one of its own pages says 2019) and matches companies with vetted developers across web, data, AI and DevOps. Candidates take Codility-based skills tests, then sit in-depth technical interviews with Proxify's senior engineers that include live coding and practical problems. The company quotes an acceptance rate of 1–3%, though the figure varies from page to page. Its network covers more than 5,000 professionals in over 90 countries, and it appeared on the Financial Times 1,000 list in 2025. Matching uses in-house AI tools alongside its hiring team.

N-iX

N-iX has been in business since 2002, has its registered headquarters in Malta and does most of its delivery from Ukraine, Poland and other Central European countries. Company materials cite more than 2,400 engineers and staff augmentation as one of three engagement models. It is hiring ML engineers in 2026, and one listing seeks a lead computer-vision engineer for an external expert network that conducts technical interviews, which suggests specialists take part in its screening for senior roles. The firm is large and stable, but ML is a fraction of its work.

Services and capabilities: Proxify vs N-iX

Capability Proxify N-iX
ML engineers ✓ ✓
LLM / GenAI engineers ✓ ✗
AI agent developers ✗ ✗
MLOps engineers ✗ ✓
Computer vision engineers ✗ ✓
NLP engineers ✗ ✗
Data engineers ✓ ✓
Engineer-led technical screen ✓ ✗
Fractional / part-time experts ✓ ✗
Trial before commitment ✗ ✗
Nearshore time-zone overlap ✗ ✗
Direct hire option ✗ ✗

Tech stack comparison: Proxify vs N-iX

Framework / platform Proxify N-iX
PyTorch ✓ ✓
TensorFlow ✓ N/A
LangChain N/A N/A
Hugging Face N/A N/A
OpenAI N/A N/A
AWS ✓ ✓
Azure ✓ ✓
Google Cloud ✓ ✓
Databricks ✓ ✓
Kubernetes N/A ✓

Pricing comparison: Proxify vs N-iX

Criterion Proxify N-iX
Minimum engagement Not published Not published
Engagement models Dedicated engineer, Fractional expert, Freelance contract Dedicated engineer, Dedicated team, Project delivery
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Proxify vs N-iX

Dimension Proxify N-iX
Best company size Startup to mid-market Startup to mid-market
Best industries SaaS, Fintech, E-commerce Financial services, Manufacturing, Retail
Best use cases Adding a data engineer to a European fintech's analytics team, Hiring a Python ML developer for a recommender system Adding a data engineering team to an enterprise data platform, Staffing a computer-vision engineer for a manufacturing client
Typical project type Dedicated engineer Dedicated engineer

Proxify vs N-iX: pros and cons

Proxify
+ Live-coding interviews with in-house senior engineers are part of the published process
+ Most of the network is in European time zones, which suits teams in the EU and UK
+ Grew fast enough to make the Financial Times 1,000 list in 2025
- AI is one of many skill areas, and there is no AI-specific test on the record
- Acceptance-rate and network-size figures differ across the company's own pages
- Developers are contractors on the platform, not Proxify employees
N-iX
+ Large bench across several Central European countries
+ Uses outside specialists to interview for senior technical roles
+ Long history with enterprise clients
- ML is a small part of a general software business
- Headquarters is listed differently across sources
- No published rates

Who should choose Proxify?

A typical fit: adding a data engineer to a European fintech's analytics team.

Senior-engineer interviews with live coding after an automated skills test. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, E-commerce, Media, Healthcare.

Who should choose N-iX?

A typical fit: adding a data engineering team to an enterprise data platform.

Scale and two decades of history in Central European delivery. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Manufacturing, Retail, Telecom, Healthcare.

Decision matrix: Proxify vs N-iX

Your situation Recommended choice
You want a working engineer, not a recruiter, to run the technical screen Proxify
You need one specialist for a few days a week Proxify
You need several engineers working as one team Both; Proxify rates higher overall
You want to test an engineer before committing Neither publishes a trial; negotiate a short first term
Your budget is at the lower end Compare: Proxify (Not published) vs N-iX (Not published)
Your team works U.S. hours Neither lists Latin American engineers; confirm overlap hours in the contract
You may want to hire the engineer permanently later Neither lists direct hire; agree conversion terms up front

Use case fit: Proxify vs N-iX

Use case Proxify fit N-iX fit Winner
Adding a data engineer to a European fintech's analytics team Strong Strong Both equally
Hiring a Python ML developer for a recommender system Strong Limited Proxify
Adding a data engineering team to an enterprise data platform Strong Strong Both equally
Staffing a computer-vision engineer for a manufacturing client Limited Strong N-iX

Verdict: Proxify vs N-iX

Proxify (4.4/5) is the stronger overall choice for most AI Engineer Staffing projects. Senior-engineer interviews with live coding after an automated skills test.

N-iX (3.9/5) is worth a look if you need staffing a computer-vision engineer for a manufacturing client. If your situation matches that, N-iX is a competitive option.

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Proxify vs N-iX FAQ

Is Proxify better than N-iX?

Proxify (4.4/5) scores higher overall, but "better" depends on your use case. Proxify's strongest advantage: live-coding interviews with in-house senior engineers are part of the published process. N-iX's strongest advantage: large bench across several Central European countries.

How do Proxify and N-iX differ in pricing?

Proxify uses hourly rate per developer billed monthly; full-time or part-time; rates on request pricing. N-iX uses monthly per engineer or managed team; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Proxify or N-iX?

Proxify 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 Proxify and N-iX?

Proxify's primary differentiator is: senior-engineer interviews with live coding after an automated skills test. N-iX's primary differentiator is: scale and two decades of history in Central European delivery. They also differ in team size (5,000+ network members vs 2,000+), minimum engagement (Not published vs Not published), and primary industries served (SaaS, Fintech vs Financial services, Manufacturing).

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