Machine Learning Engineer

Member of Technical Staff, Machine Learning & Optimization

San Francisco, CA (Onsite)

$160,000-$250,000 + Equity

I'm working with an early-stage AI startup applying the rigor of quantitative finance and high-frequency trading to digital advertising.

The team is building an autonomous decision engine that manages ad spend in real time, using machine learning, optimization, and risk-aware decision systems to drive measurable improvements in marketing performance. They're already delivering significant efficiency gains for global customers and are scaling rapidly as they approach their next stage of growth.

This is a true end-to-end ML role. You're not training models and handing them off to another team. You'll design the algorithms, build the optimization systems, and write the execution layer that deploys capital into real markets.

You'll work on problems such as:

• Budget allocation and optimization across advertising channels

• Predictive models for customer value, performance, and spend efficiency

• Risk-aware decision systems operating in dynamic environments

• Real-time bidding, execution, and automation

• Backtesting, simulation, and strategy validation

• Monitoring, observability, and model performance in production

We're looking for engineers who have:

• Experience building and deploying machine learning systems in production

• Strong foundations in statistics, probability, optimization, and quantitative problem solving

• Experience owning ML systems end-to-end, from experimentation through deployment and monitoring

• Strong software engineering skills and experience building reliable, scalable systems

• Experience working with real-world decision systems where model outputs directly drive actions

Particularly relevant experience includes:

• Optimization systems

• Decision engines

• Quantitative modeling

• Forecasting and predictive modeling

• Algorithmic trading or financial systems

• Programmatic advertising

• Reinforcement learning

• Control systems

If you're excited by machine learning, optimization, and building autonomous systems that make real-world decisions under uncertainty, I'd love to chat.