Staff Machine Learning Engineer, MadHive

• Experience: 8+ years building production systems with 4+ years focused on ML at scale
• Education: Bachelor's in Computer Science, ML, or related field (Master's preferred, PhD welcome)
• Production ML: Proven track record deploying and maintaining ML systems serving billions of requests
• Experience combining LLM with classical ML models to solve problems more complex than RAG
• Expertise in modern ML frameworks (TensorFlow, PyTorch, JAX)
• Experience with both real-time inference and batch processing at scale
• Strong foundation in distributed systems and cloud platforms (GCP preferred)
• Ability to thrive across the ML infrastructure spectrum—from rapid prototyping to robust production systems
• Leadership: Experience mentoring engineers and driving technical decisions in cross-functional teams
• Communication: Ability to translate complex ML concepts for diverse audiences

Desirable

• Join our tech-forward buy-side advertising platform as a Staff Machine Learning Engineer, where you'll be embedded in a full-stack team revolutionizing how broadcasters and agencies serve local advertisers
• You'll shape the future of advertising technology by building ML systems that process billions of daily requests and while pioneering human-facing AI ergonomics—creating natural, hyper-collaborative interactions between humans and intelligent systems
• We're tackling complex ML problems at the intersection of advertising optimization and human-centered design:
• Campaign Intelligence: Build ML systems that optimize advertising campaigns in real-time, making billions of inferences daily across live transactions
• Data Storytelling: Transform massive-scale data streams into rich, actionable insights that empower local advertisers to compete effectively, and engage advertisers to connect novel insights from our data to facts on the ground they already know about their audiences
• AI Ergonomics Pioneer: Create ML interfaces so intuitive that users don't realize they're interacting with AI—where intelligence enhances rather than complicates workflows
• Real-time Decision Systems: Design models that make split-second decisions on bidding, targeting, and optimization while maintaining transparency and control
• Technical Leadership (80% IC work)
• Architect and implement production ML systems handling billions of daily requests with sub-second latency requirements
• Design sophisticated optimization algorithms for bidding strategies, campaign performance, and audience targeting
• Build both real-time inference pipelines and large-scale batch processing systems
• Create evaluation frameworks that balance multiple objectives: performance, cost, user experience, and advertiser ROI
• AI Ergonomics Innovation
• Pioneer natural AI interactions where machine learning seamlessly enhances user workflows
• Develop collaborative AI systems that augment human decision-making without adding cognitive load
• Design ML features that feel intuitive and require zero training to use effectively
• Technical Mentorship & Influence
• Elevate ML engineering practices across the company through mentorship and knowledge sharing
• Guide junior ML engineers on your team and throughout the organization
• Collaborate with executive stakeholders to align ML strategy with business objectives
• Partner with your full-stack team (frontend, backend, design, data) to deliver end-to-end solutions
• Clear advancement path to Principal/Distinguished IC roles or Engineering Management
• Direct exposure to executive leadership and strategic decision-making