Kargo

Director, Machine Learning Operations

Posted 13 Days Ago

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New York, NY

Senior level

AdTech

The Role

The Director of Machine Learning Operations will lead the ML Ops team to develop, implement, and oversee machine learning strategies. Responsibilities include managing ML infrastructure, deploying models, ensuring performance and scalability, and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.

Summary Generated by Built In

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: Director, Machine Learning Operations

Job Type: Full-time; 3 Days In Office
Job Location: New York, NY
Salary Range: $200,000.00 - $230,000.00 (On Target Earning)

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 Director of Machine Learning Ops will play a pivotal role in leading and shaping the Machine Learning Operations function. This individual will be responsible for managing a team in developing and implementing ML Ops strategies, overseeing the deployment and maintenance of machine learning models, and collaborating with cross-functional teams to ensure seamless integration of ML solutions into our advertising technology platform. The position requires strong hands-on experience combined with leadership skills, strategic thinking, and knowledge of industry best practices.

The Daily To-Do

Strategy and Leadership:

Develop and execute a comprehensive ML Ops strategy aligned with business goals and objectives
Provide leadership to the ML Ops team, fostering a culture of innovation, collaboration, and continuous improvement
Collaborate with senior leadership to align ML Ops initiatives with overall company strategies

Infrastructure and Deployment:

Design, implement, and manage robust ML infrastructure and deployment pipelines
Oversee the deployment and monitoring of machine learning models, ensuring scalability, reliability, and performance
Implement robust processes and infrastructure for model versioning and CI/CD for ML models
Implement architectural patterns for ML pipelines and optimization frameworks

Cross-Functional Collaboration:

Work closely with Data Science, Engineering, and Product teams to understand business requirements and translate them into ML Ops processes
Collaborate with stakeholders to ensure successful integration of machine learning solutions into the AdTech platform

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

Team Development:

Recruit, mentor, and develop a high-performing ML Ops team
Foster a culture of learning and growth, staying abreast of industry trends and emerging technologies

Qualifications

BS/MS degree in Computer Science, Data Science, or a related field preferred
In-depth knowledge of MLOps principles and best practices
5+ years experience in a leadership role within ML Ops or a related field
Strong background in machine learning, data engineering, and cloud technologies
Strong experience working with Big Data platforms (Snowflake, Databricks preferred)
Excellent command of Git and VCSl best practices
Highly proficient in developing in SQL and Python. Spark and Go skills 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
Demonstrated success in building and leading high-performing teams
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