Mid Machine Learning Engineer

Meet Genesis
Genesis Digital Solutions is a consulting and technology company that helps organizations turn ideas into measurable business impact through digital expertise and AI innovation. Founded in ****, we operate across Portugal and the United Arab Emirates, supporting clients in multiple industries with intelligent, scalable, and secure solutions. We combine strategy, engineering, and emerging technologies such as AI, Data, Web3, and Digital Product Development to drive transformation end to end. Our focus is on building practical, human-centered solutions and long-term partnerships that enable sustainable growth, innovation, and real-world results.
Your Next Challenge
We are looking for a Mid Machine Learning Engineer to help bring machine learning models into production and ensure they are reliable, scalable, and properly monitored. You will work closely with Data Scientists and Data Engineers to productionize ML solutions, build and maintain deployment pipelines, monitor models in production, and optimize their performance.
What You'll Work On
Productionize machine learning models developed by Data Scientists and deploy them reliably into production environments
Build and maintain ML-focused CI/CD and deployment pipelines
Manage machine learning models throughout their production lifecycle
Implement monitoring and basic alerting for model performance, failures, and operational metrics
Optimize model response times and overall production performance
Contribute to retraining automation initiatives and continuous improvement of ML workflows
Develop clean, structured, reusable, and testable Python code
Collaborate closely with Data Scientists and Data Engineers on model deployment and data transformation initiatives
Deploy models using Docker and/or Kubernetes
Develop and maintain model-serving APIs using FastAPI or Flask
Apply pragmatic solutions to production challenges and take ownership of operational deliverables
Contribute to the development of MLOps practices, processes, and automation from the ground up.
What We're Looking For
More than 3 years of professional experience in Machine Learning
Strong Python skills, including project structuring, reusable and testable code, object-oriented programming, and design patterns
Experience with Python testing frameworks such as pytest or unittest
Strong SQL skills for querying and manipulating data
Experience building and maintaining CI/CD pipelines using tools such as GitHub Actions 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, and Scikit-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 Azure for ML workloads
Experience building model-serving APIs using FastAPI or Flask
Strong collaboration and communication skills, particularly when working with Data Scientists and Data Engineers
Ability to take ownership of deployments, pipelines, production fixes, and operational deliverables
Strong problem-solving skills and ability to work independently with appropriate guidance.
Bonus Points
Basic knowledge of Java or Scala
Experience establishing MLOps practices in environments where infrastructure and processes are still being developed
Experience with automated model retraining
Experience with model monitoring and observability
AWS, GCP, or Azure certifications
Experience working in environments with highly scalable ML workloads.
Why You'll Stay
A workplace that values innovation and personal growth
Opportunities to work on high-impact projects for leading clients
Flexible hours and hybrid work options
Support for professional development, including training and certifications
Health and life insurance
25 days of annual leave