Mid Machine Learning Engineer

Genesis Digital Solutions | Tempo integral

Mid Machine Learning Engineer

GenesisDigital Solutions is a consulting and technology company that helpsorganizations turn ideas into measurable business impact through digitalexpertise and AI innovation. Founded in 2018, we operate across Portugal andthe United Arab Emirates, supporting clients in multiple industries withintelligent, scalable, and secure solutions. We combine strategy, engineering,and emerging technologies such as AI, Data, Web3, and Digital ProductDevelopment to drive transformation end to end. Our focus is on buildingpractical, human-centered solutions and long-term partnerships that enablesustainable growth, innovation, and real-world results.

We arelooking for a Mid Machine Learning Engineer to help bring machine learningmodels into production and ensure they are reliable, scalable, and properlymonitored. You will work closely with Data Scientists and Data Engineers toproductionize ML solutions, build and maintain deployment pipelines, monitormodels in production, and optimize their performance.

WhatYou’ll Work On

Productionize machine learning models developed by Data Scientists and deploythem reliably into production environments

Build andmaintain ML-focused CI/CD and deployment pipelines

Managemachine learning models throughout their production lifecycle

Implementmonitoring and basic alerting for model performance, failures, and operationalmetrics

Optimizemodel response times and overall production performance

Contribute to retraining automation initiatives and continuous improvement ofML workflows

Developclean, structured, reusable, and testable Python code

Collaborate closely with Data Scientists and Data Engineers on model deploymentand data transformation initiatives

Deploymodels using Docker and/or Kubernetes

Developand maintain model-serving APIs using FastAPI or Flask

Applypragmatic solutions to production challenges and take ownership of operationaldeliverables

Contribute to the development of MLOps practices, processes, and automationfrom the ground up.

What We’reLooking For

More than3 years of professional experience in Machine Learning

StrongPython skills, including project structuring, reusable and testable code,object-oriented programming, and design patterns

Experience with Python testing frameworks such as pytest or unittest

StrongSQL skills for querying and manipulating data

Experience building and maintaining CI/CD pipelines using tools such as GitHubActions or Jenkins

Understanding of MLOps fundamentals, including Git versioning, pull requests,code reviews, and ML-specific versioning practices

Experience with machine learning frameworks such as TensorFlow, PyTorch, andScikit-learn

Experience deploying machine learning models using Docker and/or Kubernetes

Understanding of model optimization and compression

Experience or familiarity with cloud environments such as AWS, GCP, or Azurefor ML workloads

Experience building model-serving APIs using FastAPI or Flask

Strongcollaboration and communication skills, particularly when working with DataScientists and Data Engineers

Abilityto take ownership of deployments, pipelines, production fixes, and operationaldeliverables

Strongproblem-solving skills and ability to work independently with appropriateguidance.

BonusPoints

Basicknowledge of Java or Scala

Experience establishing MLOps practices in environments where infrastructureand processes are still being developed

Experience with automated model retraining

Experience with model monitoring and observability

Experience working in environments with highly scalable ML workloads.

Why You’llStay

Aworkplace that values innovation and personal growth

Opportunities to work on high-impact projects for leading clients

Flexiblehours and hybrid work options

Supportfor professional development, including training and certifications

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