$165K - 215K a year
Design, develop, and deploy advanced machine learning systems to optimize advertising performance. Collaborate with global teams to build production-ready ML pipelines and drive measurable business outcomes.
Candidates should have 7+ years of software development and ML engineering experience, including 3+ years in advertising systems. Proven expertise in recommendation systems, advertising algorithms, and proficiency with Python and SQL is required.
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Lead Machine Learning Engineer, Ad Performance in California (USA). This role offers the opportunity to design, develop, and deploy advanced machine learning systems that directly influence advertising performance and user engagement at scale. You will collaborate with cross-functional global teams to build production-ready ML pipelines, optimize algorithms for ad targeting and relevance, and drive measurable business outcomes. The position emphasizes both technical depth and business impact, requiring expertise in scalable ML infrastructure, distributed data processing, and experimental evaluation. You will work in a fast-paced, high-performance environment where innovation, collaboration, and accountability are essential to success. The role combines technical leadership, hands-on development, and strategic thinking to influence the direction of ad performance systems. Accountabilities: Build and scale advertising algorithms that optimize both engagement and revenue. Design, deploy, and maintain ML infrastructure for real-time ad decisioning at global scale. Conduct rigorous experiments (A/B and multivariate tests) to evaluate model impact on KPIs. Improve ETL pipelines, monitoring, and operational reliability for ML systems. Collaborate with product, data, and engineering teams to launch high-impact ad features. Stay ahead of emerging ML/AI technologies and integrate them when they provide competitive advantage. 7+ years of software development and ML engineering experience, including 3+ years in advertising systems. Proven expertise in recommendation systems, advertising algorithms, NLP, or computer vision. Proficiency with Python, SQL, and ML frameworks such as TensorFlow or PyTorch. Experience with distributed data processing frameworks (e.g., Spark, Ray) and cloud platforms (AWS/GCP). Strong analytical and problem-solving skills with a track record of delivering measurable results. Excellent communication, teamwork, and project management capabilities. Ability to translate business requirements into scalable technical solutions that optimize revenue. Competitive base salary of $165,000–$215,000 per year. Profit-sharing bonus opportunities. Comprehensive healthcare coverage (medical, dental, vision). Remote-first work environment with global collaboration. Career growth and skill development in a high-performance, innovative setting. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1
This job posting was last updated on 10/4/2025