Mateo
Full Stack Developer
ReactNode.jsPythonTypeScriptNext.jsMongoDBAWSAIAPIs
Shakers for companies
Work with a contract Machine Learning Engineer
A certified Machine Learning Engineer who takes your model beyond the notebook: they prepare the data pipeline, train with PyTorch or scikit-learn, evaluate, and leave the system serving with MLflow, containers and watched drift.
The prototype that works locally and expires in production is the pain this solves. One specific person, chosen for their speciality, with a budget set by scope.
- Certified talent in AI and agent skills
- Meet up to 3 AI Builders in 72 h
- Flexible collaboration models
+600
European clients across different industries
Top 4%
We work with the top 4% of certified talent in our community
72 hours
Meet 3 certified candidates in under 72 h
4.7/5
Our clients' satisfaction on Trustpilot
The talent mix your company needs
At Shakers you will find AI Engineers and specialists across Tech, Product and Data
Ana
DevOps Engineer
DockerCI/CDAWSAzureKubernetesTerraformAmazon Bedrock
Lucas
Backend Developer
Node.jsPythonJavaGoPHPMySQLMongoDBDocker
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Emma
Security Engineer
Burp SuiteOWASP ZAPMetasploitNmapNessusTrivySnyk
What this profile brings to your project
A Machine Learning Engineer designs, trains and deploys machine learning models: prepares the data, trains and evaluates with Python, PyTorch or scikit-learn, and takes the model to production with pipelines, containers and monitoring. The deliverable is a system that learns, not a report.
Their boundary: the data scientist explores and decides, the AI Engineer builds on foundation models and LLMs, and MLOps industrialises what another trained. The ML Engineer takes the model from data to system.
PythonPyTorchTensorFlowscikit-learnSQLSparkMLflowDockerKubernetesCI/CDAWS SageMakerVertex AIAzure MLAirflowKafkaHugging Face
One provider. One contract. Full traceability
How Shakers works for your company
Post your project
Tell us about the model you need, the data you hold and when you want to start working on it.
You get three options
We match your brief against certified talent and introduce the three AI Builders who fit best.
The last word is yours
Meet the three specialists and choose who you collaborate with; we handle the rest.
Why work with Shakers
The advantages of adding this profile with Shakers
From notebook to production
The prototype that worked locally, now serving: pipeline with MLflow, containers and watched drift. The jump nobody documents.
Own models on your data
PyTorch, TensorFlow or scikit-learn by the case, trained on your history and judged by the business metric agreed up front.
The data triad clarified
ML, data scientist or AI Engineer? The boundary follows the pain: models and production, analysis and decision, or LLMs and RAG.
The foundation layer included
Fine-tuning, embeddings and RAG when the case asks for them: the craft today also builds on foundation models.
Continuity if the specialist moves on
If the specialist changes, the pipeline stays: experiments versioned in MLflow and another certified talent picks up the model.
Capacity without growing headcount
A Machine Learning Engineer on demand, no hiring process: they arrive on your data and your cloud and scale when the model asks.
Frequently asked questions
Any other questions? Our team will answer them.
Tell us about your ML projectWhat does a contract Machine Learning Engineer do?
They design, train and deploy models: prepare the data, train with Python and PyTorch, and take the model to production with MLflow, containers and monitoring. By project, on your data and your cloud.
Machine Learning Engineer or Data Scientist?
The data scientist explores and answers business questions; the ML Engineer builds the system that learns and ships it. Ads merge them into dual titles when a project needs data and models at once.
ML Engineer or AI Engineer?
ML works own models on your data, with pipelines and MLOps; the AI Engineer builds on foundation models: LLMs, agents and RAG. If the pain is the model, ML; if it is the AI product, AI.
Do they deliver in production or just the notebook?
The engagement closes with the model serving: versioned pipeline, container deployment and watched drift. The notebook is the middle step; the deliverable is the system the company uses.
How much does a contract Machine Learning Engineer cost?
The mechanism sets it, not a rate: seniority, sector, type of model and whether it gets billed by project or by days. Public references belong to another market; the budget closes per engagement.
Is there still demand for ML Engineers in Spain?
The drop you read about is courses, not the work: 329 active tech ads in Spain mention machine learning engineer, from Wallapop to Airbus (Shakers market analysis, n=31,957, September 2026).
What gets delivered in the first weeks
The business metric defined, the first model trained and evaluated on your data, and the production decision documented: what gets deployed, how it gets served and what gets watched when the data shifts.
A market that already titles the craft
329 active tech ads in Spain mention machine learning engineer, with literal titles crossing sectors, from '(MLOps and Forecasting)' at METRICA to '(GenAI/LLM/RAG)' at Bluetab and 'Automated Driving' at Mitsui (Shakers market analysis, n=31,957, September 2026). The market wants the whole craft: data, model and production.
Foundation models without losing the craft
Much of the work that started from zero today builds on foundation models: fine-tuning, embeddings and RAG. That does not replace the ML Engineer; it moves the starting point, and whoever masters both halves covers your project end to end.
Connect with AI specialists to build your next project
Find specialists in Tech, Product, Data to complement your team
Data Scientist
The data scientist explores and decides; the ML Engineer builds and ships. Ads fuse them into dual titles; here the boundary arrives written in.
AI Engineer
The other frontier: LLMs, agents and RAG on foundation models. If the pain is the AI product rather than the own model, their row builds that layer.
Data Engineer
The channel your data arrives through: Spark, Airflow and pipelines. When the history is not ready, their row builds the supply the model drinks from.
Python Developer
The language of the craft: pandas, APIs and automation. When the model already serves and the application around it is missing, their row builds the product.
The AI talent you need Certified by Shakers
We introduce you to three ready_to_build AI Builders in 72 hours.
