Senior ML Engineer

Key Responsibilities

• Design, develop, and deploy machine learning models that extract actionable insights from advertising performance data
• Build and optimize systems that leverage LLMs to generate natural language explanations of advertising trends and recommendations
• Create clustering and classification models to segment audiences, campaigns, and creative assets based on performance characteristics
• Develop predictive models for forecasting and optimizing ad performance, budget pacing, and ROI
• Collaborate with other engineers to design efficient data pipelines that feed our ML systems
• Work with product managers to translate customer needs into ML-powered features

Requirements

• 5+ years of experience in applied machine learning
• Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Proven experience building and deploying ML models in production environments
• Hands-on experience with various ML techniques including classification, regression, clustering, and time series analysis
• Solid understanding of statistical analysis and experimental design
• Familiarity with LLMs and their application in business intelligence use cases
• Experience with data visualization and BI tools to communicate ML insights
• Strong software engineering practices including version control, testing, and CI/CDExcellent communication skills to explain complex ML concepts to non-technical stakeholders
• Bachelor's degree in Computer Science, Statistics, Mathematics, or related field (advanced degree preferred)

Preferred Qualifications

• Experience working with advertising data or in AdTech companies
• Knowledge of major advertising platforms (Meta, Google Ads, Amazon, TikTok) and their metrics
• Experience with recommendation systems and personalization algorithms
• Familiarity with marketing attribution models and customer journey analytics
• Hands-on experience fine-tuning and prompting LLMs for specific business domains
• Experience working with large datasets and distributed computing frameworks (e.g., Spark)
• Experience with MLOps tools and practices for model monitoring and management
• Knowledge of privacy-preserving ML techniques and regulations related to digital advertising (GDPR, CCPA)

What We Offer

• Competitive salary, stock, and benefits package
• Opportunity to shape the ML strategy of a growing startup from the ground up
• Work on challenging problems at the intersection of machine learning and digital advertising
• A collaborative, inclusive, and dynamic work environment in a high-growth start-up
• Work with a set of industry veterans that have 15+ years experience from early start-ups to the biggest tech companies
• Regular opportunities to learn and grow through tech talks, conferences, and continued education
• We are an equal-opportunity employer and value diversity and inclusion at our company.