Production Machine Learning & Predictive Engineering for US Platforms
Move beyond generic AI wrappers. Senior full-stack engineer Mr Umer Malik builds, trains, and deploys custom machine learning models tailored to your proprietary company data—optimizing customer classification, dynamic pricing, and automated risk scoring under Delaware mutual NDA.
Core Capabilities & Production Deliverables
Direct architectural execution by senior engineer Mr Umer Malik with zero agency dilution.
Custom Classifier & Regression Architectures
Supervised learning models developed in Python with PyTorch and scikit-learn for automated lead scoring, churn prediction, and transaction fraud flagging.
Automated ETL & Feature Engineering
Robust automated data pipelines cleaning raw SQL logs, encoding categorical variables, and normalizing features for continuous model retraining.
Domain-Specific Fine-Tuning (LoRA/QLoRA)
Fine-tuning open-source LLMs (Llama 3, Mistral) on proprietary corporate records using parameter-efficient adapters for exact domain expertise.
Low-Latency FastAPI & ONNX Model Inference
Exporting trained models to ONNX Runtime and serving predictions via containerized FastAPI microservices with sub-30ms response times.
Automated Model Drift Monitoring (MLOps)
Automated monitoring dashboards tracking model accuracy, data distribution shifts, and triggering retraining pipelines before performance degrades.
Explainable AI & Feature Attribution
Integrating SHAP and LIME algorithms to provide transparent, explainable reasoning for every algorithmic prediction satisfying US regulatory audits.
Why US Companies Hire Umer for ML
Direct access to an engineer who bridges complex mathematics with scalable web production backends.
Sub-30ms Inference Latency
Compiled ONNX models running on lightweight cloud instances delivering real-time predictions to active web apps.
Delaware Mutual NDA Protection
Strict confidentiality agreements protecting your training data, proprietary feature weights, and business models.
Predictable Milestone Pricing
Transparent fixed pricing per model iteration in USD with zero surprise compute or hourly overages.
Synchronized US Daytime Collaboration
Direct Slack collaboration with lead architect Mr Umer Malik during your working hours.
Phased Delivery Roadmap & How This Project Runs
Structured from initial discovery call to production deployment and 100% intellectual property transfer.
Phase 01: Data Feasibility & Problem Formulation
Auditing historical data, defining success metrics (AUC/F1), and agreeing on fixed milestone quotes in USD.
Phase 02: Feature Engineering & Baseline Model Training
Cleaning data, training baseline models, and validating predictive accuracy against holdout test sets.
Phase 03: FastAPI Microservice & Containerization
Packaging models into Docker containers with optimized ONNX runtime and REST endpoints.
Phase 04: Production Deployment & Telemetry Verification
Deploying to AWS ECS, configuring automated drift monitoring, full source handover, and 30-day warranty.
US Founder Frequently Asked Questions
Clear answers on US business hours alignment, USD milestone billing, and Delaware mutual NDA protection.
How much data do we need to train a custom machine learning model? ▼
How do you deploy the trained model into our existing software stack? ▼
How do you prevent model drift over time? ▼
Are our training datasets kept secure and private? ▼
Who owns the trained model weights and feature pipelines? ▼
What warranty is included after model deployment? ▼
Great dreams deserve craftsmanship, not compromises. Let’s build yours.
US METROS & STATES ACTIVELY SERVED
© 2026 UMER XPERT. SERVING THE UNITED STATES — COAST TO COAST. All rights reserved. Contracts executed under Delaware mutual NDA.