The AI engineers
your team
has been waiting for.
Why AI projects
stall mid-build.
The talent gap in AI is real — and it compounds every quarter you wait.
Generalist engineers slow AI work down
Most engineering teams were built for web and mobile. AI projects demand a completely different skill set — ML pipelines, model evaluation, vector databases, and production inference. Your current team shouldn't have to learn on the job.
Offshore models create costly lag
Timezone misalignment kills momentum. Daily stand-ups at 9pm, asynchronous reviews that take 48 hours, and communication gaps that turn simple tasks into week-long blockers.
Recruiting AI talent takes months
The senior ML engineer you need is already employed and not actively looking. Traditional recruiting pipelines weren't built for the pace of AI product development.
Agencies send junior talent at senior prices
Most staffing firms fill headcount with whoever is available. You get someone who can run a tutorial — not someone who can architect a production ML system at scale.
Every AI role,
fully covered.
We staff the complete spectrum of AI and data engineering talent — senior profiles only.
Machine Learning Engineers
Build, train, evaluate, and deploy ML models into production systems. Fluent in PyTorch, TensorFlow, Scikit-learn, and model serving infrastructure.
AI Solutions Architects
Design end-to-end AI system architecture — data ingestion, training pipelines, inference layers, and monitoring. Think in systems, not notebooks.
LLM & Generative AI Engineers
Fine-tune and deploy large language models, build RAG pipelines, and create production-grade AI agents with tool use and memory.
Senior Data Scientists
Statistical modeling, experimentation, feature engineering, and business intelligence — turning raw data into decisions that scale.
MLOps & Platform Engineers
Keep production ML alive and improving. CI/CD for models, feature stores, drift detection, and automated retraining pipelines.
Computer Vision Engineers
Object detection, segmentation, medical imaging, video analytics — from research prototype to real-time production deployment.
Built for the
way AI teams
actually work.
Nearshore. Senior. Embedded. Fast. Four things most staffing firms can't offer together.
Your timezone, your hours
Our engineers work from Costa Rica and across LATAM — fully overlapping with US and Canadian business hours. No async delays, no 8-hour lag. Just a real working day together.
Senior-only talent, rigorously screened
Every engineer passes a multi-stage technical assessment: live coding, architecture review, and AI-specific problem sets. We don't place people who can't do the job on day one.
First engineer in 72 hours
We maintain a bench of pre-vetted AI engineers across every specialization. When you have an urgent need, we move fast — not weeks, not months.
Embedded, not outsourced
GoLabs engineers join your team. They attend your stand-ups, use your tools, contribute to your repo, and build with your culture in mind. This isn't a vendor relationship.
From need to
engineer in 5 steps.
We learn your stack
A 30-minute session with our team. We map your AI roadmap, current architecture, team gaps, and the specific profile you need.
We match from our bench
Our pre-vetted talent pool is filtered against your exact requirements — tech stack, seniority, timezone, and team culture fit.
You meet the engineers
We send 1–3 profiles within 72 hours. You interview, you choose. No commitment until you're confident.
They join your team
Your new engineer is onboarded as part of your team — in your tools, your stand-ups, your workflow. Fully embedded from day one.
We stay close
Monthly check-ins, performance reviews, and direct escalation access. We manage the talent relationship so you can focus on the work.
The AI team you
need, assembled
without the wait.
A Series B startup came to us needing three ML engineers and a data architect — immediately. Their in-house recruiter had been searching for four months. We had their team embedded and contributing within two weeks.
Your next AI engineer
is already vetted.
Tell us what you need. We will match you with a senior AI engineer who is ready to embed with your team this week.