Google Cloud & Vertex AI Services

Get individual support for your organization’s Google Cloud & Vertex AI developments.

About GCP & VertexAI:


Vertex AI is Google Cloud’s platform for building, training, and deploying machine learning models. It supports both AutoML and custom models, with tools for managing the entire ML lifecycle. Designed for scalability, it helps data scientists and machine learning engineers to create robust pipelines for production usage with built-in monitoring and versioning.


The Google Cloud Platform (GCP) not only offers Vertex AI but a variety of tools, relevant to the implementation of machine learning solutions, such as data storage and processing, pretrained model APIs, MLOps and deployment functionality as well as access to computing hardware.

Need help with Vertex AI? Konrad Schultka has solved some of the toughest ML engineering challenges in production — let’s talk.

Common ML implementation challenges


Building production-ready ML systems on Google Cloud comes with practical challenges—from monitoring performance to managing complex infrastructure. Below are key areas where Vertex AI helps streamline the machine learning lifecycle:

  • Supporting a Machine Learning model in production can be challenging, since a deployed model has to be continually checked for model or data shifts. Additionally, bugs in ML code can be hard to spot since they often only lead to degradations in accuracy, not to outright errors.

  • Data/ML Scientists working on production models need to feel safe enough to push new features and improve the model without degradation in production use

  • Modern ML models often require significant compute resources, including support for multi-GPU setups

  • Vertex AI offers solutions to support the complete model lifecycle to ensure reproducible results with active performance monitoring

    • ETL pipelines and feature store for preprocessing data

    • Serverless training pipelines for automatic model training

    • Scalable hyperparameter tuning solutions

    • Experiment tracking through Vertex AI experiments

    • Automatic deployment of inference endpoint

    • Distributed training through Ray on Vertex AI

dida services

We support organizations in building robust, scalable machine learning workflows on Google Cloud. Our services are designed to help teams make the most of Vertex AI by streamlining every stage of the model lifecycle—from data preparation to deployment and ongoing monitoring:


Setup model lifecycle in the Vertex AI ecosystem including data preparation, training, experiment tracking, hyperparameter tuning and inference deployment


Design and implement automated training pipelines with Vertex AI pipelines

Setup distributed training with Ray on Vertex AI

Automated model evaluation and deployment with integration into CI/CD processes and monitoring for model degradation

How it works

Our streamlined process ensures you receive expert machine learning support tailored to your specific needs, with a clear path from initial consultation to implementation.

We work with you through these key steps:

  • 1

    Book a 30min introductory meeting with one of our Machine Learning Engineers and tell us about your current situation / problem.

  • 2

    Based on your situation and requirements, dida will propose a lean plan on how to support your team quickly and efficiently (i.e. 1-3 days of Google Cloud Vertex AI support for approx. 1-3K EUR).

  • 3

    Within the next three working days, an experienced Machine Learning Engineer with competences in Google Cloud & Vertex AI will start working on your problem.

  • 4

    After successful completion: Evaluate the results and choose how to proceed - whether expanding our services, securing recurring monthly support, or implementing the knowledge gained to continue independently.

Who this is for

This service is best suited for data science and IT teams that… 

  • are planning on working with Google Cloud & Vertex AI and want dida to do the initial setup and integration into their projects, or

  • are already working with Google Cloud & Vertex AI and desire consultation, development support or evaluations of already developed code..

About dida

dida is a software company from Berlin, Germany, specialized in the development of  individual machine learning services. The highly technical team not only trains and optimizes neural networks, it also deploys them amongst others on Google Cloud infrastructure using Vertex AI for complex production requirements and takes care of operations, maintenance and scaling.

Since dida’s beginnings in 2018 the company uses GCP to develop their ML solutions. When Vertex AI was released in 2021, dida was amongst its early users and keeps using it for many clients, which are using Google as their computing cloud provider.

Frequently asked questions

  • Who will be working on our project?

    Depending on the desired support volume dida will provide you with 1-2 experienced Machine Learning engineers that have the most experience with this specific tool / technology / framework.

  • Who will be our main point of contact?

    The dida engineer who will lead the project will be the main point of contact so that respective engineers can directly communicate with each other. 


  • How quickly can dida’s team help us address our current challenges with Google Cloud & Vertex AI?

    After signing the contract, dida guarantees to start within the next three working days.

  • How will we communicate during the project?

    We’re open to your preferred choice of communication and organization (Email, Slack, MS Teams, Gitlab / GIthub issues, …)

  • Does dida work remotely or on-site?

    Most of dida’s work is typically performed from our office in Berlin, Germany. Nevertheless we regularly visit our clients for workshops, interim and final presentations or whenever the situation demands it. If on-site work is required, please let us know so that we can arrange it.

  • How often will we receive updates on the project?

    For short term support services you will be updated either daily or after every milestone.

  • What qualifications and experience does your team have?

    dida’s team comprises largely of scientists and engineers with backgrounds in mathematics and physics - many of them holding PhDs from prestigious institutions. The highly specialized team has 8 years of industry experience in implementing machine learning solutions. dida solves algorithmically complex problems and often tackles use cases where less specialized in-house departments previously failed. Amongst its clients are large European organizations such as Deutsche Bahn, Klöckner, Zeiss or APCOA. 

  • Are there any subcontractors involved in the service delivery?

    No, all purchased services will be provided by dida employees.

Contact us


Our team of expert engineers is available to discuss your specific machine learning requirements and provide tailored Google Cloud Vertex AI solutions.