Senior Machine Learning Ops Engineer
Coderio designs and delivers scalable digital solutions for global companies.
We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end.
We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
More information:
This is a high-impact technical role.
We are looking for a Senior Machine Learning Ops Engineer to join our team.
You will own the architecture, development, and automation of end-to-end machine learning solutions.
Operating within an established engineering team, you will be a key player in bridging the gap between data science and software engineering, evaluating cloud solutions, and deploying scalable machine learning models into production.
This is a hands-on execution role.
You are responsible for the technical health of the ML lifecycle, the performance and cost-efficiency of the cloud architecture, and delivering high-quality, scalable solutions that drive business value.
What To Expect In This Role (Responsibilities)
ML Architecture & Development: Architect and develop robust, end-to-end machine learning solutions.MLOps & Automation: Manage and automate the complete machine learning lifecycle, ensuring seamless transitions from development to production.Cross-Functional Collaboration: Collaborate closely with data engineers and data scientists to create highly scalable solutions and integrate them with other technical areas across the software development life cycle.Cloud & Architecture Strategy: Work on cloud solutions, actively evaluating the performance and cost-efficiency of potential architectures.Business Alignment:



Interact with other teams and stakeholders to deeply understand business challenges and propose effective technical solutions.Mentorship & Advocacy: Communicate technical concepts clearly and teach teams how to properly use and adopt the new developments.
Requirements
Educational Foundation: Bachelor's degree in software engineering/computer science, or proven equivalent experience in data engineering or machine learning roles.ML Deployment Mastery: Proven hands-on experience implementing and deploying machine learning solutions in production environments.Core Stack Expertise: Advanced knowledge of Python, SQL, and Spark.Tooling & Infrastructure: Strong knowledge in (or similar to) Docker, Git, Bash Scripting, FastAPI, Sagemaker Studio, Airflow, and CloudFormation.Architecture & Integration: Solid understanding of data architectures and complex systems integration.Problem Solving: Demonstrated ability to troubleshoot and solve complex software system issues.Cloud Platforms: Extensive experience with modern cloud platforms, specifically AWS and GCP.Soft Skills: Must be a team player who effectively participates within the group.
We are looking for a curious profile, a self-learner with a positive attitude, and excellent communication skills.
Nice to Have
Domain experience in payments or other complex financial systems is a huge plus.
Benefits
Long-term contract engagement with high impact and autonomy.Strategic and high-visibility role within a modern engineering culture.Opportunity to influence technical strategy, especially regarding MLOps, scalable data architectures, and cloud cost-efficiency.Collaborative international team with strong technical leadership.Adaptable, dynamic, and fast-paced work environment.
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