Q.01
How quickly can you start on my project?
We can typically kick off a new project within 1–2 weeks of signing the agreement. For urgent requirements, we can assemble a team and start within 3–5 business days.
Gel 03 · Service 17 / 27
ML DevelopmentServices
We design, train, and deploy machine learning models that turn your data into predictive insights and automated intelligence.
- Rate
- From $14/hour
- Kickoff
- 1–2 weeks
- Deliverables
- 06
How it runs
- 01Discovery
- 02Design
- 03Development sprints
- 04Testing
- 05Deployment
Step 01 / 06 · Data Engineering
Gel 03 · AI, data & automation
What you get
What wedeliver.
From data preparation to model deployment, we deliver end-to-end machine learning solutions built for production.
- Not yet01
Data Engineering
Included
<DataEngineering />Data collection, cleaning, feature engineering, and pipeline automation.
- Not yet02
Model Development
Included
<ModelDevelopment />Custom ML models using supervised, unsupervised, and reinforcement learning.
- Not yet03
Deep Learning
Included
<DeepLearning />Neural networks for complex tasks like image recognition and NLP.
- Not yet04
Model Deployment
Included
<ModelDeployment />Production deployment with APIs, batch processing, and edge inference.
- Not yet05
MLOps & Monitoring
Included
<MlopsMonitoring />Automated pipelines with model versioning, A/B testing, and drift detection.
- Not yet06
Transfer Learning
Included
<TransferLearning />Leverage pre-trained models to accelerate development and reduce data requirements.
At wrap
- Predictive Analytics. Forecast trends, demand, and outcomes with accurate machine learning models.
- Anomaly Detection. Automatically identify unusual patterns in data for fraud detection and quality control.
- Classification & Clustering. Categorize data, segment customers, and discover hidden patterns automatically.
- Time Series Analysis. Analyze temporal data for demand forecasting, stock prediction, and capacity planning.
- Model Optimization. Fine-tuned models that balance accuracy, speed, and resource consumption.
- MLOps Pipeline. Automated model training, validation, and deployment pipelines for continuous improvement.
Why Malkano
Why Malkano for ML Development?
06 frames · one crew
- Take 01
PhD-level data scientists and ML engineers
- Take 02
End-to-end ML lifecycle management
- Take 03
Production-grade model deployment and monitoring
- Take 04
Experience across tabular, image, text, and time series data
- Take 05
Cost-efficient training with cloud and edge optimization
- Take 06
Transparent model evaluation with clear metrics and reporting
On the stack · 16
- Python
- TensorFlow
- PyTorch
- scikit-learn
- XGBoost
- Pandas
- NumPy
- AWS SageMaker
- Azure ML
- MLflow
- Kubeflow
- Apache Spark
- Airflow
- DVC
- Weights & Biases
- ONNX
Before you ask
Questions
Q.02
What engagement models do you offer?
We offer three models: Fixed Price (ideal for well-defined projects), Time & Material (for evolving requirements), and Dedicated Team (for long-term partnerships). We'll recommend the best fit during consultation.
Q.03
Do you provide post-launch support?
Yes, every project includes post-launch support. We offer flexible maintenance packages ranging from basic bug fixes to full managed services with 24/7 monitoring and SLA guarantees.
- Prod.
- Malkano Tech
- Scene
- 17
- Take
- 01
Ready to Leverage Machine Learning?
Turn your data into a competitive advantage with custom ML solutions. Get a free consultation.
FRAME 11 — Contact
Have a project?Let's build.
Tell us what you're building. We reply within one business day with next steps and a rough plan, for teams in the USA, Canada and India.
Studio 1 · Rec
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