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Kargo unites the world's leading brands, retailers and premium publishers across screens using innovative technology and advanced creative ad formats. At Kargo, we bring together the best of the best with a spark of creativity to stand out from the crowd, and we celebrate the diversity of our employees. As an equal‑opportunity employer, we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, veteran status or disability. Individuals with disabilities are provided reasonable accommodation to participate in the application process and perform essential job functions. Please contact us to request an accommodation.
Title: Staff Machine Learning Engineer
Job Type: Permanent (Remote)
Job Location: Dublin, Ireland
Opportunity
We are looking for a Staff Machine Learning Engineer to help us design and deploy scalable machine learning and optimization systems that directly contribute to our advertising revenue.
Team
The Machine Learning Engineering (MLE) team at Kargo bridges the gap between data science, engineering, and production deployment. Our mission is to design, deploy, monitor, and maintain scalable machine learning and optimization systems that directly contribute to the business’s revenue objectives. We collaborate closely with Data Science, Product Management, and Business stakeholders, focusing on solutions that optimize auction dynamics, predict advertising outcomes, and enable advanced recommendations.
Role
The Staff Machine Learning Engineer will design, develop, deploy, and maintain machine learning models, ensuring seamless integration into our advertising technology platform. The position requires strong hands‑on experience, technical skills, and a deep understanding of machine learning principles and best practices.
Daily To-Do
Design, develop, and deploy machine learning models to meet business objectives.
Implement CI/CD pipelines for seamless model versioning, updates, and deployment.
Ensure models are scalable, reliable, and optimized for production environments.
Collaborate with Data Science, Engineering, and Product teams to deliver end-to-end ML solutions.
Work with stakeholders to integrate models into the AdTech platform.
Set up monitoring and alerting systems to track model health and identify data/model drift.
Continuously optimize models for improved efficiency, accuracy, and performance.
Leverage AWS (EMR, EC2, SageMaker), Snowflake, Databricks, and other cloud tools for ML workflows.
Optimize data pipelines, incorporating feature stores for enhanced model performance.
Stay current with industry trends and emerging technologies.
Contribute to knowledge sharing, code reviews, and process improvements.
Qualifications
BS/MS in Computer Science, Statistics, or a related field preferred.
In-depth understanding of machine learning principles and best practices.
6+ years of experience in building and deploying machine learning models in production environments.
Experience building both offline and online training and inference pipelines for real‑time systems.
Strong experience with AWS (S3, EC2, Lambda, SageMaker), Snowflake, and other cloud-based tools for machine learning and data engineering.
Familiarity with the MLOps stack, including Databricks, Feature Stores, Kubernetes, Kubeflow, MLflow, etc.
Expertise in Spark for large-scale data processing and distributed workflows.
Proficient in Git and version control best practices.
Highly skilled in SQL and Python; experience with Go is a plus.
Hands‑on experience in automating the provisioning and management of cloud infrastructure.
Strong interest in advertising, media, analytics, and marketing, with AdTech or digital advertising experience preferred.
Highly organized, detail-oriented, and able to manage multiple tasks effectively.
Excellent communication skills, able to convey complex technical concepts to both technical and non-technical audiences.
Able to work independently and collaboratively within a team environment.
Follow Our Lead
Big Picture: kargo.com
The Latest: Instagram (@kargomobile) and LinkedIn (Kargo)
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Industries
Advertising Services
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