Careers at Bigabid

Bigabid is an innovative technology company led by data scientists and engineers devoted to mobile app growth. Our proprietary ad platform is powered by machine learning and is constantly improving its distribution algorithms.

We deliver valuable results and insights for a fast-growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies. 

Our ever evolving, state-of-the-art machine learning technology analyzes tens of TB of raw data per day to produce millions of ad recommendations in real-time. This data is used to power machine Learning predictions, business critical metrics, and analytics used to power our decision making process.

As we continue to push the boundaries of AI-driven advertising, We are looking for an experienced ML product manager to join our product department and lead the evolution of our ML-based product capabilities.

In this role, you’ll work cross-functionally with Data Scientists, Engineers, BI, and Product peers to develop and scale ML solutions that power our DSP – enhancing ad targeting, budget allocation, real-time bidding, attribution, and measurement. You’ll own the roadmap and strategy for AI/ML features and help translate complex technical models into impactful business outcomes.

Responsibilities:

• Own the ML Product Roadmap: Define and prioritize AI/ML initiatives that align with business goals and drive measurable impact.
• Bridge Product and Data Science: Translate model concepts into product requirements and ensure smooth execution from research to production.
• Drive Experimentation: Lead A/B testing efforts to validate model performance and ensure optimizations directly improve advertiser outcomes.
• Define Success Metrics: Connect technical ML metrics (e.g., model accuracy, recall, latency) to business KPIs (e.g., ROAS, eCPM, LTV).
• Collaborate on AI Infrastructure: Partner with Data Science and Engineering to enhance our ML pipeline efficiency, scalability, and monitoring.
• Ensure Model Adoption: Work closely with client-facing teams to ensure ML-driven products are adopted and drive tangible campaign value.
• Stay Ahead: Keep up with industry trends in ML, LLMs, recommendation systems, and MLOps to maintain a competitive edge.