This is us

At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.

This is the job

 We are seeking a highly skilled Senior MLOps Engineer to take ownership of a globally deployed recommender system that already delivers significant value across many countries. This is a senior, hands-on role where you will actively contribute to the codebase while influencing strategy, architecture, and best practices for ML systems at scale.

This is you

• 5+ years of professional experience as a Machine Learning Engineer, with a strong track record of deploying and maintaining production systems.
• Practical expertise with MLflow for experiment tracking and model management, and GitLab CI/CD for automation.
• Proven experience designing scalable ML systems in cloud environments (AWS preferred).
• Proven ability to design and document complex ML and data pipeline architectures.
• Strong mentoring background, providing guidance to data scientists, data engineers, and MLOps engineers.
• Programming skills in Python and familiarity with the wider data science ecosystem.
• Hands-on experience building, training, and deploying models on AWS SageMaker.
• Proficiency with at least one major deep-learning framework (TensorFlow, PyTorch).

Nice-to-have skills:

• Master’s or PhD in Computer Science, Machine Learning, or related field.
• Familiarity with advanced model monitoring and observability tools (Prometheus, Grafana, Evidently AI).
• Excellent communication skills with the ability to explain complex technical concepts to diverse audiences.

This is your role

• Lead the architectural evolution of our live recommender system, enhancing its scalability, capabilities, and overall quality.
• Drive the strategy and execution of MLOps practices, including building and optimizing CI/CD pipelines in GitLab, implementing robust monitoring, and using MLflow to ensure reproducibility of ML workflows.
• Collaborate with data scientists to productionalize advanced ML models on AWS SageMaker, meeting strict performance, reliability, and scalability standards.
• Act as a technical leader and mentor, guiding data scientists and engineers on system design, software engineering best practices, and model deployment strategies.
• Contribute hands-on to the Python codebase, writing clean, maintainable, and well-tested code for data pipelines, ML infrastructure, and model deployment.
• Work closely with product managers, data scientists, and business stakeholders to translate business needs into actionable technical solutions.
• Proactively identify and introduce new technologies to strengthen our ML and AI capabilities.

What awaits you at Avenga?

Through our values, Better Minds, Bolder Ideas, and Bigger Hearts, we strive to provide you with the tools, autonomy, trust, and assistance you need to excel. Enjoy benefits like private health insurance, well-being programs, flexible and hybrid work models, laptops and gear, training, language classes, social events, great offices, and more.

We take pride in the diverse skills and character of our teams, welcoming everyone to apply and contribute to our collective strength.