About Bloomside

Bloomside is a community built for the AdTech ecosystem.

We partner with innovative companies across the advertising technology landscape to connect them with exceptional talent. Our focus goes beyond filling roles; we aim to build long-term relationships and support the growth of a strong global AdTech community.

Through our network and industry expertise, we help fast-growing companies hire professionals across engineering, data, product, and commercial teams.

About the role

One of the companies in our AdTech network is looking for a Machine Learning Engineer to help design and build intelligent systems that improve the efficiency, safety, and performance of digital advertising.

In this role, you will work on machine learning models and data-driven systems that analyze large-scale datasets to detect patterns, classify content, and support decision-making across advertising platforms. These systems may power areas such as fraud detection, brand safety, content classification, and media quality analysis.

You will collaborate with data scientists, engineers, and product teams to develop scalable ML solutions and bring models into production environments.

What you’ll do

Design, train, and deploy machine learning models for large-scale data environments.
Build systems that detect patterns and anomalies in advertising data.
Develop models for tasks such as fraud detection, content classification, and media quality analysis.
Work with large datasets to extract signals that improve advertising performance and safety.
Build and maintain ML pipelines for experimentation, training, and model deployment.
Collaborate with engineering and data teams to integrate ML systems into production environments.
Monitor model performance and continuously improve model accuracy and reliability.

What we’re looking for

Strong experience with Python and machine learning libraries such as Scikit-learn, PyTorch, or TensorFlow.
Experience developing and deploying machine learning models in production environments.
Solid understanding of statistical modeling, classification, and anomaly detection techniques.
Experience working with large datasets and distributed data systems.
Familiarity with data processing tools such as SQL, Spark, or BigQuery.
Experience collaborating with engineering teams to integrate ML systems into products.
3–5+ years of experience in machine learning, data science, or a related field.

Nice to have

Experience working in AdTech, MarTech, or programmatic advertising.
Experience building models for fraud detection, content moderation, or brand safety.
Experience with NLP or large-scale content classification systems.
Familiarity with MLOps tools for model monitoring, experimentation, and versioning.
Experience working with cloud environments such as AWS or GCP.

Why join

Work on large-scale data and machine learning problems within the digital advertising ecosystem.
Contribute to systems that improve transparency, safety, and efficiency in programmatic advertising.
Collaborate with experienced teams building innovative technology products.