Machine Learning Development
We engineer the 85% around the model — pipelines, deployment, monitoring, and retraining — that makes ML survive production.
Partnering with Leading Brands Across the Globe
Trusted by leading brands worldwide, we deliver scalable digital solutions that drive innovation, performance, and measurable business impact.
Your Model Works. Your ML System Doesn't — Yet.
A model that scores 92% in testing is a science experiment, not a product. The moment it meets live data — messy inputs, drift, edge cases — accuracy erodes until a business metric drops. We close that gap: we build the full system around the model and measure it against the decision it's meant to drive. The model is the variable; the system is the asset.
What We Engineer in Machine Learning Development
Data pipelines and feature engineering
reliable, monitored data in; garbage designed out.
Custom model development
classification, regression, forecasting, recommendation, and ranking.
Computer vision and NLP models
from document understanding to image and signal analysis.
Training, tuning, and honest evaluation
measured against business metrics, not just accuracy.
Deployment and serving
real-time APIs, batch, or edge, integrated into your apps.
MLOps and monitoring
drift detection, alerting, and automated retraining.
Model optimization
faster inference and lower compute cost without losing quality.
The Numbers Behind Our Engineering
How We Deliver
Frame and feasibility
define the decision the model serves and the metric that proves it works.
Data audit and pipeline
assess, clean, and engineer reliable data flows.
Model development and honest evaluation
benchmark against the real-world bar, not the lab bar.
Productionize and integrate
deploy, wire into your systems, and instrument for observability.
Operate and improve
monitor drift, retrain, and tune over time.
Already have a model stuck in "almost"? We'll review it and map the path to production in a free 30-minute session.
Book a free ML scoping callIndustries We Cover
Healthcare & Life Sciences
HIPAA-aware ML for clinical data, diagnostics, and patient-flow prediction.
Banking, Financial Services & Insurance
Fraud detection, risk and credit scoring, and demand forecasting under strict compliance.
Retail & eCommerce
Recommendation engines, demand forecasting, dynamic pricing, and churn prediction.
Logistics & Supply Chain
Route optimization, ETA prediction, and inventory forecasting at scale.
Manufacturing
Predictive maintenance, automated quality inspection, and yield optimization.
Public Sector & Law Enforcement
Secure, auditable ML for high-stakes, regulated environments.
Case Studies That Prove It
Ways to Work With Us
Fixed-scope project
a clear deliverable, timeline, and price for a defined ML build.
Dedicated ML pod
an embedded team of data scientists, ML and MLOps engineers that scales with you.
Staff augmentation
plug senior ML talent into your existing team and tooling.
ML consulting and audit
feasibility, model review, or a production-readiness assessment.
Our ML Stack
Languages and frameworks
Python · PyTorch · TensorFlow · scikit-learn · XGBoost
Platforms
AWS SageMaker · Azure ML · Google Vertex AI
Data and MLOps
Snowflake · Databricks · Airflow · MLflow · Docker · Kubernetes
GenAI / LLM
LangChain · Llama · GPT · Pinecone · FAISS
Why Teams Choose QSS for ML
We ship systems, not notebooks
The model is 15%; we engineer the 85% that survives production.
CMMI Level 5 + ISO 27001 delivery
Process and security maturity most boutique AI shops can't match.
Regulated-industry depth
Healthcare, finance, and public-sector experience where mistakes are expensive.
Real GenAI/ML in production, not demos.
Full ownership and transparency
Your code, your models, your IP, always.
One team, end to end
Data, model, deployment, and ops under one roof.
Frequently Asked Questions
It depends on scope. A focused pilot typically starts in the low tens of thousands; a full production system with data pipelines and MLOps scales from there. We scope and price each engagement up front — no open-ended billing.
A scoped pilot usually ships in weeks, not quarters — enough to prove value before a larger build. Production hardening and MLOps follow from there.
Yes, we do this often. We take a working prototype and engineer the 85% that gets it live and keeps it stable.
Completely. Everything is yours on delivery, under NDA from day one.
Start with a free scoping call. We then propose scope, timeline, and an engagement model — fixed project, dedicated pod, or staff augmentation.
We deliver under ISO 27001 and CMMI Level 5, with secure and self-hosted options so sensitive data stays in your environment.
Let's Turn Your Model Into a System.
Tell us the decision you're trying to automate, and we'll show you the fastest credible path to production.
Book a free ML scoping call