Staff Machine Learning Engineer

Reposted 17 Days Ago
Be an Early Applicant
Dublin
In-Office
Mid level
AdTech • Digital Media • Marketing Tech • Mobile
Art. Tech. Results.
The Role
The Staff Machine Learning Engineer will design, develop, deploy, and maintain machine learning models, collaborating with teams to integrate solutions into the advertising technology platform.
Summary Generated by Built In

Kargo unites the world's leading brands, retailers and premium publishers across screens using innovative technology and advanced creative ad formats. At Kargo, we're all about bringing together the best of the best with a spark of creativity to stand out from the crowd. The same is true for our employees. What makes Kargo and each Kargo team member exceptional makes our company special. Kargo believes differences should be celebrated and is committed to diversity in the workplace. 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, protected veteran status, disability or other legally protected status. Individuals with disabilities are provided reasonable accommodation to participate in the job application process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Founded in 2003, Kargo is a global company headquartered in New York with offices around the world.

Title:  Staff Machine Learning Engineer

Job Type: Permanent, Remote

Job Location: Dublin, Ireland

The Opportunity

The 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. Collaborating closely with Data Science, Product Management, and Business stakeholders, we focus on delivering robust solutions that optimize auction dynamics (e.g., bid pricing, pacing), ensure accurate predictions of advertising outcomes (CTR, viewability, etc.), and enable advanced recommendations for advertising content (audience targeting and contextual matching).

The Role: The Staff Machine Learning (ML) Engineer will play a crucial role in designing, developing, deploying, and maintaining machine learning models. This individual will work closely with cross-functional teams to ensure the seamless integration of ML solutions 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.

The 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)

Top Skills

AWS
Databricks
Ec2
Emr
Go
Kubeflow
Kubernetes
Machine Learning
Mlflow
Python
Sagemaker
Snowflake
Spark
SQL
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The Company
HQ: New York, NY
620 Employees
Year Founded: 2003

What We Do

Kargo creates breakthrough cross-screen ad experiences for the world’s leading brands and publishers. Every day, our 600+ employees bring the power of their creativity and diversity to radically raising the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Humble brag: In 2024, Kargo was recognized as a Best Place to Work by Built In.

Why Work With Us

The key to our success is our people. We’ve built a community that values teamwork, is not afraid to take chances and relentlessly strives to disrupt the industry and stand out from the crowd. Diversity is fundamental to the Kargo culture as we celebrate and embrace our differences in our inclusive workplace. Founded in 2003, Kargo is headquartered

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Kargo Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
HQNew York, NY
Melbourne, AUS
Brisbane, AUS
Sydney, AUS
Singapore
Auckland, NZ
Austin, TX
Chicago, IL
London, UK
Santa Monica, CA
Waterford, Ireland
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