Senior Machine Learning Engineer

About Us 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: http://coderio.com

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.
• Flexible, dynamic, and fast-paced work environment.

Why Join Coderio? At Coderio, we value talent and excellence. We are a remote-first company, and this specific strategic role offers the opportunity to drive high-stakes initiatives from anywhere. We are passionate about technology, collaboration, and fair compensation. We offer an inclusive and challenging environment with real growth opportunities. If you are motivated to design solutions that make a difference, we are waiting for you. Apply now.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.