Machine Learning Engineer

Kargo creates breakthrough cross-screen ad experiences for the world’s leading brands and publishers. Everyday, 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 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:  Machine Learning Engineer 

Job Type: Permanent
Job Location: New York
Salary Range: $160,000 - $180,000

The Opportunity:

The Team: The Data Science team at Kargo researches, develops, deploys and maintains ML and optimization models to deliver solutions integral to the business’ revenue goals. We work in close collaboration with Engineering, Product Management and business teams to develop solutions to optimize auction dynamics (bid pricing, pacing, etc), predict advertising outcomes (CTR, viewability, etc), and recommend advertising content (audience targeting and contextual matching recommendations).  

The Role: The 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:

1. Model Development and Deployment:

Design, develop, and deploy machine learning models to address various business needs.

Implement robust processes and infrastructure for model versioning and CI/CD for ML models.

Ensure scalability, reliability, and performance of deployed models.

1. Collaboration:

Work closely with Data Science, Engineering, and Product teams to understand business requirements and translate them into end to end ML solutions.

Collaborate with stakeholders to ensure successful integration of machine learning solutions into the AdTech platform.

1. Monitoring and Optimization:

Establish and maintain monitoring and alerting systems to ensure the health and performance of deployed models.

Implement optimization strategies to enhance model efficiency and accuracy over time.

1. Infrastructure and Tools

Design, implement, and manage ML infrastructure and deployment pipelines.

Work with Big Data platforms (AWS Stack (EMR, EC2, Sagemaker), Snowflake, Databricks preferred) and cloud technologies to support ML workflows.

1. Continuous Improvement::

Stay abreast of industry trends and emerging technologies.

Participate in code reviews, knowledge sharing, and continuous improvement initiatives.

Qualifications : 

• BS/MS degree in Computer Science, Data Science, or a related field preferred.
• In-depth knowledge of machine learning principles and best practices.
• 3+ years of experience in a machine learning or data science role.
• Strong background in machine learning, data engineering, and cloud technologies.
• Experience in building end-to-end ML pipelines, from data ingestion to model deployment and monitoring.
• Strong experience with AWS services (S3, EC2, Lambda, SageMaker, etc.) for machine learning and data engineering tasks.
• Strong experience with Big Data platforms (AWS Stack, Snowflake, Databricks).
• Proficiency in Spark for large-scale data processing.
• Excellent command of Git and version control best practices.
• Highly proficient in SQL and Python. Spark and Go skills are a plus.
• Hands-on experience in automating the provisioning and management of cloud infrastructure.
• A strategic thinker with a deep interest in advertising, media, analytics, and/or marketing.
• AdTech & Digital advertising experience preferred.
• Highly organized and detail-oriented, capable of juggling several tasks at once.
• A strong communicator, with both technical and non-technical audiences.
• Able to work independently and as part of a team.

Follow Our Lead

• Big Picture:  kargo.com
• The Latest:  Instagram (@kargomobile) and LinkedIn (Kargo)