AI Services / Machine Learning Engineering
ML systems that work in production — not just on Wednesday demos
We design, train, and deploy ML systems — classical and deep — that hold up under production load. Tabular, time-series, vision, and NLP pipelines with MLOps baked in: versioning, eval, monitoring, and retraining.
Why Empiryx
Why our ML survives production rotations
Expertise
What we build
01
Tabular ML
GBMs, gradient boosting, and tree ensembles for high-noise tabular data.
02
Time-series
Forecasting for demand, signals, fraud, and ops.
03
Vision
Classification, detection, and segmentation tuned to your visual domain.
04
NLP
Classifiers, embeddings, and fine-tuned LLMs for text-heavy tasks.
Expertise
Roles & capabilities we specialise in
A deeper look at the specialists we place and the work they ship.
Feature engineering
Provenance-tracked features, distributed feature stores, reuse-first design.
Eval harnesses
Golden sets, regression nets, and A/B routing before any model ships.
Training pipelines
Reproducible training runs on Kubeflow, Airflow, or managed platforms.
Serving
Low-latency serving with batching, caching, and warm-start patterns.
Drift monitoring
Data drift, performance drift, and label drift alerts as first-class events.
Retraining
Scheduled or triggered retraining tied to drift thresholds, with rollback safety.
Industries we serve
Built for high-stakes sectors
Domain-aware engineers who understand your sector's constraints — not just the syntax.
FinTech
Fraud, credit, churn models
Retail
Demand forecast and personalization
Manufacturing
Quality and predictive maintenance
Healthcare
Risk and signal models within approved scope
FAQ
Answers to common questions
Process
How it works
Feasibility & data
We study the data, the eval criteria, and whether ML is even the right answer.
Baseline + vertical
We ship a baseline model with eval harness end-to-end — usually 2–3 weeks.
Tune & ship
We tune to your acceptance bar with continuous eval, then deploy to production.
Operate
We monitor drift, retrain on schedule, and report on real-world performance.
Get started
ML that survives production — and retraining rotations
Bring the data. We'll bring the features, the evals, and the MLOps.
Explore more
Hire AI Developers in India
Pre-vetted ML, NLP, LLM & CV engineers. Onboard in 7–10 days.
Offshore Development Team India
Dedicated offshore engineering team embedded in your workflows.
ODC & GCC Setup India
Start with an ODC. Evolve into a fully owned GCC as you scale.
Hire Machine Learning Engineers
ML Engineers, Data Scientists, NLP & MLOps specialists in India.
Build Engineering Team in India
Full-team formation — frontend, backend, AI/ML, DevOps, and leads.
AI Automation
n8n, Zapier & custom workflows that run your business on autopilot.
AI Engineering
RAG, fine-tuning, and AI agents built for production, not demos.
MLOps
Model serving, monitoring, and CI/CD for machine learning systems.
DevOps
CI/CD, infrastructure as code, and observability that scales.
Application Scaling
Performance audits and fixes that take your MVP to production-ready.
Database & Data Engineering
Database design, pipelines, and migrations built to last.