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/ Fractional Teams /

Hire Machine Learning Engineers

Hire machine learning engineers from Neural AI. Experienced ML engineers for model development, MLOps, feature engineering, and production ML systems in Malta.

Book a free consultation → See how it works
/ the solution /

Hire Machine Learning Engineers built around your business.

Every solution we deliver is built on three pillars: your data, your context, and continuous improvement. Each capability is traceable and measurable.

  • Model Development & Deployment Expertise

    Our machine learning engineers bring deep experience in supervised and unsupervised learni…

  • MLOps & Production Infrastructure

    Specialised in deploying models with robust CI/CD pipelines, automated retraining schedule…

  • Feature Engineering & Data Science

    Expert feature engineering that extracts maximum predictive power from available data asse…

  • Experiment Tracking & Reproducibility

    Disciplined experimental methodology with comprehensive tracking, model versioning, hyperp…

/ how it works /

Live in weeks, not months.

We analyse your project requirements, technology stack, and team structure to define the precise ML engineering skills needed. This ensures you get engineers whose expertise matches your problem domain and infrastructure.

From our Malta-based bench of ML engineers, we identify candidates with relevant domain experience, framework proficiency, and production deployment track records. You review profiles and select the best fit.

Selected engineers integrate into your workflows within days, not weeks. We handle secure access provisioning, codebase familiarisation, and alignment with your engineering standards and sprint cadence.

Engineers deliver working models and ML infrastructure iteratively, with regular demos and checkpoint reviews. Continuous feedback loops ensure output meets your technical and business requirements precisely.

Throughout the engagement, engineers document architectures, model decisions, and operational runbooks. Structured knowledge transfer ensures your internal team can maintain and extend ML systems independently.

Post-engagement, Neural AI provides optional support packages for model monitoring, retraining, and scaling. Scale the team up or down as your ML project portfolio evolves.

/ what you get /

Everything you need. Nothing you don't.

Model Development &
Deployment Expertise
MLOps &
Production Infrastructure
Feature Engineering &
Data Science
Experiment Tracking
& Reproducibility
/ built for your situation /

Sounds familiar?

Startup CTO
"We can't afford a full-time AI team but we have real AI projects that need experienced engineers — how does fractional AI staffing actually work in practice?"

We assign a dedicated Neural AI engineer to your project on a day-rate or monthly retainer, embedded in your team, working in your tools, and delivering production-ready code — no agency overhead.

How Neural AI helps

We assign a dedicated Neural AI engineer to your project on a day-rate or monthly retainer, embedded in your team, working in your tools, and delivering production-ready code — no agency overhead.

/ proof /

Real deployments. Real results.

AI & NLP

Grocery Price Monitoring ML System

An AI-powered system using web scraping and GPT-based NLP for product name matching across Maltese supermarkets, enabling real-time food price comparisons with predictive modelling for pricing trends.

95% prediction accuracy

Read case study →
AI & Computer Vision

Smart Video Classification Pipeline

AI-driven solution organising 13,000+ educational videos for eSkola by automating transcription, classification by subject and academic year, and enabling keyword search.

80% processing time reduction

Read case study → AI Solution

Hotel Contact Finder Automation

70% manual effort eliminated

Read case study →
/ questions /

Hire Machine Learning Engineers FAQ

What experience level do your ML engineers have?
Our machine learning engineers have between five and fifteen years of professional experience, with backgrounds spanning research, startups, and enterprise environments. Each engineer holds relevant certifications from AWS, Google Cloud, or Azure and has deployed multiple production ML systems across industries including iGaming, finance, and healthcare.
How quickly can an ML engineer start on my project?
Most engagements begin within one to two weeks of signing. Our Malta-based team maintains a bench of pre-vetted ML engineers ready for immediate deployment. For urgent requirements, we can onboard engineers within five business days with expedited security and access provisioning.
What engagement models do you offer for ML engineers?
We offer full-time embedded, part-time fractional, and project-based engagement models. Full-time engineers integrate into your team daily, while fractional arrangements provide senior ML expertise at a fraction of the cost. Project-based engagements suit well-defined deliverables with clear timelines and milestones.
How do your ML engineers integrate with our existing development team?
Our engineers adopt your existing tools, processes, and sprint cadence from day one. They participate in standups, code reviews, and planning sessions. We use collaboration platforms like Jira, Confluence, Slack, and GitHub to ensure seamless integration with your development workflows.
What ML frameworks and platforms do your engineers specialise in?
Our engineers are proficient in TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, and Hugging Face Transformers. They also have deep expertise in MLOps platforms including MLflow, Kubeflow, AWS SageMaker, Google Vertex AI, and Azure Machine Learning for end-to-end model lifecycle management.
How do you ensure quality and accountability for hired ML engineers?
Every engagement includes regular performance reviews, code quality metrics, and milestone-based deliverable tracking. Our Malta-based engineering managers provide oversight and ensure engineers meet your standards. If an engineer is not the right fit, we offer a replacement guarantee within the first thirty days.
Can I hire multiple ML engineers for a larger project?
Absolutely. We frequently provide ML engineering squads of two to five engineers for larger initiatives. These teams include complementary specialisations such as feature engineering, deep learning, and MLOps, ensuring comprehensive coverage across all aspects of your machine learning programme.
What is the cost structure for hiring ML engineers through Neural AI?
Pricing is based on engagement model and seniority level. Fractional arrangements start at competitive day rates, while full-time embedded engineers are priced monthly. All pricing is transparent with no hidden fees, and you can scale up or down with thirty days notice to align with project needs.
/ get started /

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