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SoftBlues
Google Cloud PartnerOfficial Partner
Hire ML Engineers

Hire Machine Learning EngineersWho Ship to Production

Access ML engineers who don't just build models -they deploy, monitor, and maintain them. From data pipelines to production inference, get specialists who understand the full ML lifecycle.

End-to-End ML Expertise
Production Focus
Senior Engineers Only
Why Hire

Why Machine Learning Requires Specialised Talent

The gap between a working Jupyter notebook and a production ML system is enormous. Data scientists build models; ML engineers make them work reliably at scale.

Bridge the Production Gap

Our ML engineers specialise in taking models from research to production -handling the 90% of work that happens after training.

Build Sustainable Systems

Get ML infrastructure that doesn't break: proper pipelines, monitoring, retraining workflows, and documentation.

Optimise for Business Impact

Engineers who understand that model accuracy means nothing without business value. ROI-focused ML development.

Capabilities

Machine Learning Expertise Across the Stack

Predictive Modeling

Regression, classification, time series forecasting, and survival analysis for business prediction needs.

Deep Learning

Neural networks for complex pattern recognition: CNNs, RNNs, Transformers, and custom architectures.

Feature Engineering

Transform raw data into predictive signals. Domain expertise combined with automated feature discovery.

Model Optimization

Hyperparameter tuning, architecture search, quantization, and pruning for performance and efficiency.

ML Infrastructure

Training pipelines, feature stores, model registries, and serving infrastructure that scales.

Monitoring & Maintenance

Drift detection, performance monitoring, A/B testing frameworks, and automated retraining.

Technology Stack

Technologies Our ML Engineers Master

Core ML

scikit-learnXGBoostLightGBMCatBoostTensorFlowPyTorch

NLP & Vision

Hugging FacespaCyNLTKOpenCVtorchvision

Data Engineering

Apache SparkPandasPolarsBigQueryAirflow

MLOps

MLflowKubeflowMetaflowDockerKubernetes

Model Serving

TensorFlow ServingTorchServeTritonBentoML

Cloud Platforms

Vertex AISageMakerAzure MLDatabricks
Use Cases

Machine Learning Solutions We Deliver

Demand Forecasting Systems

Predict inventory needs, staffing requirements, and resource allocation with time series ML models.

Fraud Detection Pipelines

Real-time anomaly detection systems that identify fraudulent transactions, accounts, or behaviours.

Recommendation Engines

Personalised product, content, or action recommendations based on user behaviour and preferences.

Quality Control Systems

Computer vision for manufacturing defect detection, visual inspection, and quality assurance.

Ready to Build Your Team?

Tell us what you need. We'll match you with the right developers, walk you through our process, and have candidates ready within days.

2-Week Onboarding
Fast integration with your team
No Long-Term Lock-in
Flexible engagement terms
Senior Engineers Only
5+ years average experience
FAQ

Frequently Asked Questions