AI Nearshore Staff Augmentation
Experienced AI Engineers Who Build, Integrate, and Scale Intelligence Inside Your Team
AI Roles
We Provide
We augment your team with specialized AI professionals, including:
- AI Engineers
- Machine Learning Engineers
- Data Scientists
- Data Engineers
- NLP Engineers
- Computer Vision Engineers
- AI Solution Architects
- MLOps Engineers
Artificial Intelligence Talent, Not Just Technology
Artificial Intelligence only creates value when it’s applied correctly. At Square Codex, we don’t sell abstract AI concepts or black-box tools, we provide experienced nearshore AI engineers who know how to apply artificial intelligence inside real production environments.
Our engineers work as an extension of your in-house team, using your tools, processes, and standards. From model development to deployment and optimization, we help you move faster without the complexity of traditional hiring.
Whether you’re building AI products, automating operations, or enhancing data-driven decision-making, our nearshore AI talent gives you the expertise you need, exactly when you need it.
Why Square Codex for
AI Staff Augmentation
Nearshore AI expertise that scales with your business
- Senior-level AI engineers
Our talent pool includes experienced AI and machine learning engineers with hands-on production experience. - Fast and flexible hiring
Skip long recruitment cycles. Add AI engineers to your team in days, not months. - Seamless team integration
Our engineers work within your workflows, attend your meetings, and collaborate as part of your team. - Cost-effective nearshore model
Access top AI talent while reducing hiring costs and operational overhead. - Scalable engagement models
Scale up or down as your AI initiatives evolve.
AI Technologies
Our Engineers Master
Applied AI across modern architectures and frameworks
Our nearshore engineers actively work with the most relevant AI technologies and models in today’s ecosystem:
Machine Learning & Deep Learning
- Supervised and unsupervised learning
- Neural networks and deep learning architectures
- Model training, evaluation, and optimization
Large Language Models (LLMs)
- GPT-based models
- Open-source LLMs
- Prompt engineering and fine-tuning
- Retrieval-Augmented Generation (RAG)
Natural Language Processing (NLP)
- Text classification and sentiment analysis
- Entity recognition and document processing
- Conversational AI and chatbots
Computer Vision
- Image classification and object detection
- Facial and pattern recognition
- Video analysis and automation
Predictive Analytics
- Demand forecasting
- Risk and anomaly detection
- Behavioral modeling
MLOps & Deployment
- Model versioning and monitoring
- CI/CD for AI pipelines
- Cloud-based AI infrastructure