Ad Server Product Manager Level 2

Responsibilities

Kforce has a client in Cincinnati, OH that is seeking an Ad Server Product Manager Level 2. Summary: This team will play an integral part in advancing our advertising solutions by implementing Machine Learning models into our Ad Serving Process to better meet shopper and advertiser needs. This includes developing an automated and scalable pipeline to leverage machine learning algorithms, alongside Data Science and Engineering teams. This is a long-term effort with multiple phases. It provides diverse opportunities for team members to learn and grow with the work. The systems involved are key revenue drivers for the organization. Team members could work in a collaborative environment while delivering impactful capabilities. Responsibilities include:

• Develop & manage a short/long term roadmap & strategy to scale machine learning models in production through an automated pipeline
• Understand & communicate business objectives and current technical infrastructure to ensure deployments are scalable and stable
• Outline customer/business problems and technical challenges associated with the scope of work to aide in discovery and development
• Contribute to/lead discovery & inception sessions to assess scope of work
• Utilize data and understanding of business objectives, stakeholder feedback, and technical dependencies to prioritize work across deploying, monitoring, and maintaining pipeline
• Maintain relationships with stakeholders to instill open lines of communication to share feedback, learning, and objectives
• Coordinate releases with core teams to ensure a seamless deployment that is on time and meets requirements
• Continuously monitor performance to ensure models continue to meet KPIs over time and adapt, as needed
• Lead requirements gathering and management of backlog, alongside development team
  
  

Requirements

• 5-10 years in ML engineering, MLOps, or ML product management, (with a proven track record in Vertex AI and cloud-based ML deployment) Vertex AI experience can be more like 12-18 months
• Experience operating within Cloud Experiences, Vertex AI
• Machine Learning & MLOps: Strong expertise in managing the ML lifecycle, from training to production deployment, using automated pipelines
• Cloud & Infrastructure: Extensive experience with Google Cloud Platform (GCP), especially Vertex AI, including managed pipelines, feature store, model monitoring, and AutoML
• Automation & Scalability: Expertise in scaling ML models using CI/CD pipelines, containerization (Docker, Kubernetes, Vertex AI Pipelines), and model versioning
• Software Engineering & DevOps: Knowledge of infrastructure as code (Terraform, Helm), microservices, and API-driven model deployment
• Performance Monitoring & Adaptation: Experience with Vertex AI Model Monitoring, Cloud Logging, and A/B testing to ensure continuous model effectiveness
  
  

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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