Staff Machine Learning Engineer

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 raise 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 Ad Age and Built In.

Who We Hire

Success takes all kinds. Diversity describes our workforce. Inclusion defines our culture. 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, perform essential job functions, and receive other benefits and privileges of employment.

Title: Staff Machine Learning Engineer

Job Type: Permanent

Job Location: New York

Salary Range: $180,000 - $200,000

The Opportunity

The Team: The Machine Learning Operations (MLOps) 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.
• 3 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)