I Will Build And Deploy Custom Machine Learning Models And Mlops Pipelines — Per Hour

I Will Build And Deploy Custom Machine Learning Models And Mlops Pipelines — Per Hour - Image 2

QUICK OVERVIEW

End-to-end machine learning engineering — from data preprocessing and model training to cloud deployment on GCP and Hugging Face. Deep learning, computer vision, NLP, predictive modelling, and time-series forecasting, all handled across the full MLOps lifecycle.

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machine_learning

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✔ Verified⭐ Zinner Level 1✋ Human Only

PH From Philippines

📅 Zinner Since Mar 2026

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cloud deployment data preprocessing machine learning mlops predictive modelling

I will build and deploy custom machine learning models and MLOps pipelines — per hour

From $37.003 packages available

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✦SINGLE HOUR

$37.00No platform fees ⓘ

1 hour of professional machine learning engineering. Ideal for initial consultations, project scoping, code reviews, or small focused tasks. Message me before ordering.

2-day delivery1 Revision

1 hour of ML engineering time
Project scoping or code review
Written summary of findings or recommendations
Follow-up message with next steps

One-time payment

Subscribe & Save 5%$35.15/month — billed monthly, cancel anytime

✦5 HOUR BLOCK

$185.00No platform fees ⓘ

5 hours of dedicated ML engineering for contained builds — data preprocessing, model prototyping, feature engineering, or deploying an existing model. Message me before ordering.

7-day delivery2 Revisions

5 hours of ML engineering time
Data preprocessing or feature engineering
Model prototyping or training
Source code delivered
Progress updates throughout
Written documentation of work completed

One-time payment

Subscribe & Save 5%$175.75/month — billed monthly, cancel anytime

✦10 HOUR BLOCK

$370.00No platform fees ⓘ

10 hours of end-to-end ML engineering for substantial builds — full training pipelines, cloud deployments, or complete proof-of-concept systems. Message me before ordering.

10-day delivery3 Revisions

10 hours of ML engineering time
Full end-to-end pipeline development
Model training, evaluation, and optimisation
Cloud deployment (GCP or Hugging Face)
All source code and documentation
Progress updates throughout
Post-delivery support guidance

One-time payment

Subscribe & Save 5%$351.50/month — billed monthly, cancel anytime

✓ Single Hour — $37.00 selected

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PAYMENT METHODS

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At a Glance

Key details about this service to help you decide. Generated by Zinn Hub, not the seller.

MLOps Coverage

Full Lifecycle

Covers data engineering, model training, evaluation, CI/CD, and cloud deployment on GCP or Hugging Face - end-to-end, not just modelling.

Core Specialisms

CV, NLP, Forecasting, GenAI

Computer vision, NLP, time-series forecasting, predictive modelling, and RAG/LangChain GenAI applications all within scope.

Tech Stack

Python, TensorFlow, MLflow, Docker, GCP

Full stack: TensorFlow, Keras, Scikit-Learn, Pandas, NumPy, MLflow, Docker, GitHub Actions, GCP, and Hugging Face.

Delivery Format

Production-Ready Code + Docs

Source code, model files, and written documentation delivered per project. Buyer retains full ownership of all code and models.

What You'll Receive

Formats:

Custom Code

Delivery Method: Order Manager

Video Type: Presale

Notes: I will write clean professional and well document code for you.

Full Description

I build and deploy complete, production-ready machine learning systems that solve real business problems — not just prototypes that sit in a notebook gathering dust.

With 15 years of professional experience as a creative lead before transitioning into machine learning engineering, I bring something most ML engineers don't: a strategic, business-first perspective. I don't just build models — I understand why you need them and what they need to achieve commercially. That means every system I deliver is designed with your actual operational goals in mind, not just technical accuracy metrics.

My expertise spans the entire MLOps lifecycle. I handle everything from raw data engineering and feature extraction through to model training, evaluation, and full CI/CD deployment on Google Cloud Platform or Hugging Face. You don't need to hire separate people for data prep, modelling, and deployment — I deliver the complete pipeline.

My core specialisms include predictive modelling for forecasting business outcomes, computer vision and deep learning using convolutional neural networks, natural language processing for text analysis and language understanding, time-series forecasting for demand planning and operational prediction, and GenAI applications including RAG pipelines and LangChain integrations.

Real projects I've built and deployed include an anomaly detection system using autoencoders and mel spectrograms for predictive maintenance (shortlisted at ITEC Beijing), an end-to-end migraine prediction app deployed on Hugging Face, a restaurant demand forecasting model for inventory optimisation, a CNN-based plant disease classifier deployed on GCP with a live frontend, and an AI-powered homework grading application for the education sector.

My tech stack includes Python, TensorFlow, Keras, Scikit-Learn, Pandas, NumPy, MLflow, Docker, GitHub Actions, GCP, and Hugging Face — everything needed to take a concept from raw data to a live, scalable, deployed system.

This Zinn is priced per hour. Please message me before ordering so we can scope your project, estimate the hours required, and make sure we're aligned on deliverables before you commit. Then simply select the number of hours as your quantity at checkout.

Let's turn your data into a deployed solution that actually works.

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Compare Packages

Feature	Single Hour	5 Hour Block	10 Hour Block
Delivery Time	2 days	7 days	10 days
Revisions	1	2	3
1 hour of ML engineering time	✓	✕	✕
Project scoping or code review	✓	✓	✓
Written summary of findings or recommendations	✓	✕	✕
Follow-up message with next steps	✓	✕	✕
5 hours of ML engineering time	✕	✓	✕
Data preprocessing or feature engineering	✕	✓	✕
Model prototyping or training	✕	✓	✕
Source code delivered	✕	✓	✕
Progress updates throughout	✕	✓	✓
Written documentation of work completed	✕	✓	✕
10 hours of ML engineering time	✕	✕	✓
Full end-to-end pipeline development	✕	✕	✓
Model training, evaluation, and optimisation	✕	✕	✓
Cloud deployment (GCP or Hugging Face)	✕	✕	✓
All source code and documentation	✕	✕	✓
Post-delivery support guidance	✕	✕	✓

Samples

View examples of the seller's work related to this Zinn.

My Showcase

Portfolio

Examples of the seller's work related to this Zinn.

End To End App

Audio processing end to end app, for boat engine anomaly detection

Homework Grading AI App

Homework Grading AI App hosted on GCP and using Gemini Models

Extra Information

My Skills

Python:Yes

TensorFlow:Yes

Keras:Yes

Scikit-Learn:Yes

Deep Learning:Yes

Predictive Analytics:Yes

RAG pipelines:Yes

LangChain:Yes

Prompt Engineering:Yes

Data Preprocessing:Yes

Feature Engineering:Yes

Pandas:Yes

NumPy:Yes

Statistical Modeling:Yes

GCP:Yes

MLflow:Yes

Docker:Yes

GitHub Actions (CI/CD):Yes

API Development & Integration:Yes

Machine Learning & AI:Yes

GenAI & LLMs:Yes

Data Science:Yes

Cloud & MLOps:Yes

Service Details

Service Type

Standard

Zinner Type

Freelancer

Availability

24/7

Seller's Country

Philippines

Languages Accepted

EnglishFilipino (Tagalog)

NDA available

Yes

Project Sizes Handled

Any Size

Response time

Same day

Years of Experience

10+

Frequently Asked Questions

Why do I need to message you before ordering?

Because every ML project is different. I need to understand your data, your business problem, and your expected outcomes before I can give you an accurate estimate of the hours required. A quick scoping conversation ensures you only pay for what you actually need and that we're fully aligned before any work begins.

How do the hourly packages work?

Each package represents a block of hours at my hourly rate. You select the package that best fits your project scope, and the quantity selector lets you multiply if you need more hours. For example, ordering 2x of the Standard package gives you 10 hours. We'll agree on the exact scope and hours before you place your order.

What if my project needs more hours than estimated?

We'll discuss this during the scoping phase. If a project grows beyond the original estimate, I'll let you know before any additional hours are worked so you can decide how to proceed. I never charge for time we haven't agreed on.

Do I need to provide my own data?

Yes. You'll need to provide the dataset or data source for your project. During our scoping conversation I'll advise on data requirements, formatting, and any preprocessing that might be needed before we start.

What programming languages and frameworks do you use?

My primary stack is Python with TensorFlow, Keras, Scikit-Learn, Pandas, and NumPy. For MLOps I use MLflow, Docker, GitHub Actions, and deploy on Google Cloud Platform or Hugging Face. If your project requires a specific framework, let me know during scoping.

Will I own the code you produce?

Yes. All source code, models, and documentation produced during your project are delivered to you and are yours to use, modify, and deploy as you see fit.

Can you work with my existing codebase or models?

Absolutely. Whether you need an existing model improved, retrained, or deployed to production, I can pick up where you or a previous developer left off. Just share what you have during our scoping conversation.

What industries have you worked in?

My deployed projects span healthcare, agriculture, food and beverage, education, and industrial maintenance. That said, machine learning principles apply across all industries — if you have data and a business problem, I can engineer a solution.

Do you provide ongoing support after delivery?

The Premium package includes post-delivery support guidance. For ongoing maintenance or monitoring beyond that, we can discuss a separate arrangement during our scoping conversation.

What's the difference between this Zinn and your Senior ML & Data Science Zinn?

This service is ideal for focused, well-defined ML tasks at a competitive hourly rate. My Senior ML & Data Science Zinn is for more complex projects requiring deeper architectural expertise, advanced system design, CI/CD pipeline setup, and full production-grade deployment — reflected in the higher rate.

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I will build and deploy custom machine learning models and MLOps pipelines — per hour

At a Glance