[ Vetted AI engineering talent ]
We're an AI development company. Every engineer in our network is vetted on real production work, not take-home assignments, so you get people who can build and ship from day one. Hire a single developer or a full dedicated team, on an hourly, monthly, or fixed price basis, whichever suits your project.
The kind of teams that hire through us
Capabilities
One network, six specializations. Hire a single engineer for one of them, or bring in a dedicated team that covers all six.
Chat assistants, copilots and RAG pipelines built on GPT, Claude, Gemini and open-source models, with evaluation built in from day one.
Custom models for prediction, ranking and recommendation, trained and tested against your actual business metrics, not textbook benchmarks.
Detection, segmentation, OCR and visual inspection systems that run on the cloud or on the edge, from first prototype to live production.
Classification, extraction, summarization and search over your documents, tuned to your domain and to more than one language where needed.
CI/CD for models, monitoring, drift detection and cost-efficient serving on AWS, GCP or Azure, so your models keep working long after launch.
AI embedded into your existing product: APIs, data plumbing, guardrails and UX, delivered by engineers who also write backend and frontend code.
Chat assistants, copilots and RAG pipelines built on GPT, Claude, Gemini and open-source models, with evaluation built in from day one.
Custom models for prediction, ranking and recommendation, trained and tested against your actual business metrics, not textbook benchmarks.
Detection, segmentation, OCR and visual inspection systems that run on the cloud or on the edge, from first prototype to live production.
Classification, extraction, summarization and search over your documents, tuned to your domain and to more than one language where needed.
CI/CD for models, monitoring, drift detection and cost-efficient serving on AWS, GCP or Azure, so your models keep working long after launch.
AI embedded into your existing product: APIs, data plumbing, guardrails and UX, delivered by engineers who also write backend and frontend code.
How you hire
Hiring AI developers with us means choosing a shape, not a headcount. Most clients start with one engineer and grow into a dedicated team as the project grows. Every option can be hired hourly, monthly, or on a fixed price basis.
Need a single specialist, not a whole hiring project? We match one vetted AI or ML engineer to your stack and your timezone.
Need a pod that can own a roadmap end to end? We put together a small dedicated team under one contract and one point of contact.
The network
Vetted AI and ML engineers. Every profile below shows the production experience behind it.
Aiko Tanaka
Senior LLM Engineer
8 yrs · ex-Rakuten
Fine-tunes and serves production LLMs, with a focus on retrieval accuracy and eval pipelines.
Andrés Torres
MLOps Architect
10 yrs · ex-Mercado Libre
Designs ML platform infrastructure that scales training and serving to hundreds of models.
Carlos Rivera
Computer Vision Engineer
7 yrs · ex-Cornershop
Ships production computer vision pipelines for retail and logistics workflows.
Diego Vargas
NLP Research Engineer
6 yrs · ex-Globant
Takes NLP research to production, from custom tokenizers to domain-tuned embeddings.
Elena Petrova
ML Platform Engineer
9 yrs · ex-Yandex
Builds feature stores and training infrastructure that hold up at scale.
James Okafor
Data Engineer, ML Pipelines
8 yrs · ex-Flutterwave
Builds real-time data pipelines that keep ML systems fed with clean, timely data.
Lena Fischer
AI Product Engineer
6 yrs · ex-N26
Ships AI features end-to-end, from prototype to production-grade UI.
Marcus Johnson
Applied AI Engineer
7 yrs · ex-Stripe
Applies LLMs to internal tooling and support automation with measurable impact.
Maria Santos
Generative AI Engineer
6 yrs · ex-Globo
Builds diffusion and generative pipelines for media production at scale.
Mateus Costa
MLOps Engineer
7 yrs · ex-Nubank
Runs CI/CD for ML, plus the monitoring and rollback systems that keep models safe in prod.
Nguyen Thi Lan
Deep Learning Engineer
8 yrs · ex-VNG
Trains and optimizes deep networks for speech and vision workloads.
Priya Sharma
Senior ML Engineer
10 yrs · ex-Freshworks
Leads ML systems from data to deployment across cross-functional teams.
Ravi Patel
AI Infrastructure Engineer
9 yrs · ex-Zoho
Builds GPU infrastructure and serving layers for demanding model workloads.
Sofia Morales
Research Engineer, NLP
5 yrs · ex-Rappi
Builds evaluation and fine-tuning pipelines for domain-specific language models.
Valentina Cruz
AI Solutions Engineer
6 yrs · ex-Globant
Scopes and delivers client-facing AI integrations from kickoff to launch.
Why Hire AI Developers
We're an AI development company, not a marketplace or a recruiter. The average in-house AI hire still takes 5+ months, and one in three doesn't work out. Here's what we do differently.
Our four-stage screening tests engineers on the kind of work you'll actually pay them for — designing, shipping and maintaining real ML systems. Fewer than 4 in 100 applicants pass.
Because vetting happens before you arrive, we skip straight to matching. You interview 2–3 pre-qualified engineers, not a pipeline of résumés.
Guaranteed 4+ hours of daily overlap with your core hours. Engineers work in your repos, your Slack and your standups, like your own team, minus the hiring overhead.
NDA before any technical conversation. Full IP assignment in every contract. Code lives in your repositories from the very first commit.
If the first two weeks don't convince you, you pay nothing, and we replace the engineer at no cost. Our retention rate says you won't need to.
Add an MLOps specialist for launch month, or move to part-time after. Two weeks' notice, no penalties, no renegotiation.
Process
Day 0
A 30-minute call with a technical lead, not a salesperson. We map your stack, your skills gap and your timeline.
Day 2
Within 48 hours, you get 2–3 profiles pre-vetted for your exact need. Interview them however you like.
Week 1
Your engineer joins your team, your repos and your rituals. The first two weeks are free if it turns out not to be a fit.
Ongoing
Add specialists, extend hours, or bring in a full dedicated team. One agreement, one point of contact, hired hourly, monthly, or fixed price.
Stack coverage
Engineers are matched by stack, not just by title, so onboarding is measured in days.
# Models & frameworks
PyTorch
custom training loops, distributed runs
TensorFlow
production serving, TF Serving pipelines
Keras
rapid prototyping, transfer learning
Hugging Face
pretrained model hub, transformers
scikit-learn
classical ML, feature pipelines
NumPy
vectorized numerical computing
pandas
dataframes, data wrangling
# LLM & GenAI
Claude
reasoning-heavy agents, long-context tasks
Google Gemini
multimodal generation, Google-native stacks
LangChain
RAG orchestration, agent chains
Ollama
local/self-hosted model serving
Mistral AI
open-weight models, cost-efficient inference
vLLM
high-throughput LLM serving
Redis
caching, low-latency vector lookups
# Data & infrastructure
Apache Spark
large-scale batch & stream processing
Apache Kafka
real-time event streaming
Apache Airflow
pipeline orchestration & scheduling
ClickHouse
real-time analytics at scale
PostgreSQL
transactional data + pgvector search
MongoDB
document + vector storage
Snowflake
cloud data warehousing
# MLOps & cloud
Google Cloud
managed compute & storage
Databricks
unified data + ML lakehouse
Grafana
metrics dashboards, alerting
Kubernetes
container orchestration, autoscaling
MLflow
experiment tracking, model registry
Docker
reproducible build & deploy
Terraform
infrastructure as code
Engagement models
Choose how you work with us. Every model includes vetting, matching and replacement guarantees.
Rate on request
Most common
Rate on request
Quote on request
Beyond staffing
A named technical lead owns delivery, not just introductions
Scope and milestones are set before work starts, not renegotiated mid-project
You get shipped software and post-launch support, not just a matched engineer
Industries
Engineers who have shipped in your industry already know its data, constraints and regulators.
Fraud detection, credit scoring, document intelligence and compliant LLM assistants.
Clinical NLP, medical imaging and patient triage assistants, built with privacy first.
Recommendation engines, demand forecasting, visual search and pricing models.
AI copilots, in-product assistants, semantic search and workflow automation.
Visual inspection, predictive maintenance and route optimization on the edge.
Delivery platforms, restaurant ordering systems and demand forecasting for cloud kitchens.
Booking assistants, guest management, location insights and virtual concierge tools.
Applicant tracking, resume screening, interview analytics and workforce prediction.
Property listing platforms, virtual tours, CRM workflows and automated lease management.
Fan engagement apps, ticketing optimization, athlete training tools and performance dashboards.
Adaptive e-learning platforms, virtual classrooms, assessment tools and LMS systems.
Networking apps, content discovery engines, moderation tooling and community analytics.
Delivery, ride-hailing, booking assistants and subscription management tools.
Solutions
We embed AI into your existing systems: model integrations, language tools, vision pipelines and chat interfaces, built to hold up in production.
01
We integrate AI and ML models into your existing platforms, so you get predictions and automation without rebuilding what's already there.
02
Semantic search, entity extraction and document intelligence, tuned to your domain vocabulary and multilingual where needed.
03
GPT, Claude and Gemini embedded into your product as copilots and assistants, with guardrails built in from day one.
04
Image, audio and video recognition pipelines for inspection, moderation and content understanding at production scale.
05
Custom chatbots for support, sales and internal ops, trained on your data and wired into the tools your teams already use.
06
Fine-tuning and deployment of open-source and proprietary LLMs for domain-specific reasoning, retrieval and generation tasks.
Comparison
| Hire AI Developers | In-house hiring | Freelance marketplaces | |
|---|---|---|---|
| Time to start | Under 1 week | 5+ months | 1–4 weeks |
| Technical vetting | 4-stage, by senior AI engineers | Your team's time | Self-reported profiles |
| Cost of a bad hire | Zero, free replacement | Significant cost, months lost | Your risk |
| Recruiting fees | None | 20–30% of salary | 15–20% platform markup |
| IP & NDA handling | Standard in every contract | Standard | Varies per freelancer |
| Scale team up/down | 2 weeks' notice | New hiring cycle | Re-search each time |
Case files
LLM · Fintech
A Series B payments company needed to cut support load without hurting CSAT. Two Hire AI Developers engineers built a RAG assistant over their help center and transaction data.
Computer vision · Manufacturing
An electronics manufacturer replaced manual inspection with edge models running at 30fps across 12 production lines, staffed by one vision engineer and one MLOps specialist.
MLOps · SaaS
A recommendation-driven marketplace was overpaying for GPU inference. A Hire AI Developers MLOps architect re-platformed serving with batching, quantization and autoscaling.
Trust & compliance
The legal and security groundwork is done before your project starts, not negotiated after.
Mutual NDA signed before we discuss your architecture, data or roadmap. Standard, not an upsell.
Everything built during the engagement belongs to you, assigned in writing in every contract.
Engineers work inside your repos, your VPN and your access controls, with an offboarding checklist on every exit.
Identity verification and background checks on every engineer before their first client engagement.
Training data never leaves your environment. We support GDPR, HIPAA and SOC 2-aligned workflows.
One agreement covers every engineer on your project, no separate paperwork or ambiguity per freelancer.
FAQ
Most clients meet 2-3 matched, pre-vetted engineers within 48 hours of the first call, and have someone starting inside a week.
Every engineer goes through a four-stage screening process that tests them on real production work, not puzzles. Fewer than 4 in 100 applicants pass.
Everything from LLM applications and RAG pipelines to computer vision, NLP, MLOps and full AI product integrations. If it involves shipping AI to production, we likely have an engineer for it.
Yes. Alongside single developers, we also put together dedicated teams — typically an ML engineer, a backend engineer and an MLOps specialist — under one contract and one point of contact.
We work on three simple bases: hourly, monthly, or fixed price for a clearly defined scope. There are no recruiting fees on top, and every model already includes vetting, matching and a replacement guarantee.
You do. A mutual NDA is signed before any technical conversation, and full IP assignment is written into every contract.
The first two weeks are risk-free. If it isn't working out, you pay nothing for that period, and we replace the engineer at no extra cost.
Yes. We guarantee at least four hours of daily overlap with your core working hours, so standups and reviews can happen live.
[ Start here ]
One short form. A technical lead reads it, assigns the right AI developer from our team, and replies within one business day, with a developer ready to start, not a sales deck.
Prefer to talk first? We answer fast.