Machine Learning Engineer

Member of Technical Staff — Machine Learning & Optimization

📍 San Francisco | 💰 $180K–$250K + Equity

An early-stage AI company is building an autonomous decision engine to optimize large-scale digital marketing spend using machine learning and quantitative optimization techniques.

We’re looking for a Machine Learning Engineer / MTS to design predictive models, optimization algorithms, and production systems that drive automated decision-making across digital platforms.

You’ll work at the intersection of machine learning, optimization, and real-world execution systems, developing models that influence how significant budgets are allocated and deployed.

What You’ll Do

• Develop predictive models that estimate value and inform decision strategies
• Build optimization systems that allocate resources across competing objectives
• Design infrastructure that executes algorithmic decisions through production systems and APIs
• Create simulation and testing environments to evaluate new strategies before deployment
• Own the lifecycle of ML systems from experimentation through production monitoring

Who You Are

• 4+ years of experience applying machine learning to real-world problems
• Strong understanding of statistics, probability, and mathematical modeling
• Experience deploying models into production environments
• Comfortable building scalable systems and integrating with external APIs
• Able to rapidly prototype solutions and iterate based on real-world performance

Nice to Have

• Experience with optimization techniques such as convex optimization
• Background in quantitative systems, marketplaces, or algorithmic decision systems
• Experience working in early-stage startup environments

Compensation & Benefits

• $180,000 – $250,000 salary
• Meaningful early-stage equity
• Health, dental, and vision coverage
• Flexible PTO
• Relocation support