Hire a machine learning engineer remotely

Hire a machine learning engineer remotelySmarter models, live faster

Imagine: an experienced machine learning engineer who turns your data into working models. From data collection to training and deployment in production, everything is carefully built and tested.

Post your job for free, online within 2 minutes.

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Machine learning engineer die modellen traint en analyseert achter meerdere schermen

What a machine learning engineer does for you

Building models that actually work

From data exploration to training and validation, your engineer delivers models that demonstrably contribute to your goals.

Deployment in production

Models are not only built but also deployed to production in a stable and scalable way, with attention to maintenance.

Knowledge of the latest AI tools

Your engineer is trained in the latest AI tools and keeps up with new techniques relevant to your application.

How much does it cost to
hire a machine learning engineer?

A freelancer often works just 16 hours a week and an agency typically charges for 8 hours of effort, while a full-time machine learning engineer at Remote Opus works on your models 40 hours a week.

FreelancerAgencyOpus
Hours p/week16 hours8 hours40 hours
Monthly amount€ 2,250€ 1,950€ 1,295

Your engineer is fully onboarded into your data, systems and goals. Because he or she is available full-time, there is room left for related tasks such as data analysis or maintaining pipelines. That way you get more out of your investment than model development alone.

Why a machine learning engineer on board?

Machine learning demands deep, sustained attention to data, training and validation. A full-time engineer builds that knowledge up step by step, while a freelancer is often only available to a limited extent.

Full focus on your data and goals

Instead of generic solutions, a dedicated engineer delivers models tailored to your specific business processes.

Experiences of clients
who outsourced their growth

Onze specialisten werken met AI
Trained in AI

All our specialists are trained in AI

Every Opus specialist works with the latest AI tools every day. That way you optimize your processes, run your operations more efficiently and get more work done in the same amount of time. You do not just get better results from your machine learning models, you make your entire way of working smarter and faster.

  • Smarter and faster processes through AI
  • More efficient business operations
  • More work done in the same time
Global team

Your team, worldwide

We have offices worldwide where international top talent works for your company. Every specialist becomes fully immersed in your organization, while we take care of the daily floor management at our offices.

Frequently asked questions about
Hire a machine learning engineer remotely

A full-time machine learning engineer through Remote Opus costs from 1,295 euros per month. That is a fixed monthly amount, with no agency fees or long-term contracts.

Within roughly 14 days we match you with a suitable engineer, who then gets straight to work on your machine learning models.

Yes, the engineer becomes part of your team and you direct the day-to-day work yourself. Behind the scenes we take care of coaching, contracts and payroll administration.

You get working models with clear reporting on accuracy and performance. You often see the first usable results within a few weeks.

Yes, think of data analysis, setting up data pipelines or support with data visualization.

Yes, your engineer can analyze existing models and improve them on accuracy, speed or scalability.

Yes, your engineer works with tools such as Python, TensorFlow, PyTorch or cloud platforms like AWS and Azure.

Ready to get started

Ready to scale?

Post your job for free today and we will match you with international top talent. You only pay when you hire someone.

Free and without obligation, no commitments.
Het Remote Opus team aan het werk
4.8/5
rating from employers

Directly schedule your introduction

Pick a time that suits you. We'll discuss your data and goals and how we build a working model for them.

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Approach

This is how your machine learning engineer approaches it

From data analysis to a working model in production.

1

Analyzing data and objectives

Your engineer maps out which data is available and what result the model needs to deliver.

2

Building and training the model

Different models are trained and tested for accuracy and reliability.

3

Implementing and monitoring

The model is deployed to production and continuously monitored, with clear reporting on performance.

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