AI Engineer, Optimisation & Intelligence | San Francisco (Onsite) | $200K–$300K base

AI Engineer, Optimisation & Intelligence | San Francisco (Onsite) | $200K–$300K base

We've partnered with one of the fastest-growing AI startups in San Francisco, building an autonomous growth platform that runs paid customer acquisition end to end. Their agents replace the traditional media-buying stack, letting companies run paid acquisition across the major ad platforms without human media buyers. The traction is exceptional and remarkably capital-efficient: around $30M in revenue growing roughly 30% month on month, all on a lean $10M raised, with live spend running across Meta, Google, TikTok and Snapchat for customers in mobile, gaming, AI and tech. They are now raising a Series A on the back of it. It is a small, flat, high-talent team winning on results rather than noise.

This is a rare opportunity to own the intelligence layer of the product, the part that actually decides what happens to a campaign. A dedicated platform team builds the simulator and the tooling; you own the decisions, the policy and the learning loop. Because the system manages real ad spend, every decision you design is graded against returns within days, not quarters. You'll report directly to a hands-on, technical CTO who is in the code daily, work with genuine autonomy, and get the intellectual pull of quant-style optimisation applied to live ads rather than a trading book. If you're the kind of engineer already tinkering with something new this week, you'll feel at home.

The Role

As an AI Engineer on the intelligence layer, you will:

• Build the decision engine: recommendation and scoring systems for bid changes, budget reallocation, pause and boost calls, and postback optimisation.
• Design the learning loop that defines how the system learns from outcomes, so campaign strategy compounds over time rather than resetting.
• Write the optimisation policies over noisy live data, from simple rule-based strategies through post-training and reinforcement learning.
• Orchestrate multiple agents reasoning over campaign context, design how they work together, and evaluate what they produce.
• Own the number: you are accountable for decision quality and what the spend returns, not for platform plumbing or simulator infrastructure.

Explore our comprehensive directory of visa sponsorship jobs from employers worldwide who are ready to sponsor talented international professionals.

About You

• You have shipped a closed-loop decision or optimisation system in production, and you can point to the method you used and the metric it moved.
• You are hands-on with optimisation over noisy, live data using techniques such as reinforcement learning, bandits, post-training or rule-based strategy.
• You have direct experience with ads mechanics such as bidding, budget and ROAS, rather than only search or ranking systems.
• You are comfortable designing and orchestrating multiple agents that reason over context, and evaluating their output.

Interested in opportunities specifically in United State? Discover our dedicated Visa Sponsorship Jobs in United State page featuring roles from top employers in this location.

• You have a recent production track record, ideally with systems shipped in the last year and a strong GitHub or production history working with live data.
• You thrive on autonomy and ownership, and you have a genuine bias toward building.
• One of these backgrounds fits you: an ML engineer who has owned a production closed-loop optimisation system, a quant or RL and bandits specialist moving into applied ads optimisation, or an ads-optimisation engineer who has worked directly on live spend.
• You are based in or willing to relocate to San Francisco and happy to work onsite. Visa sponsorship is available, including OPT and H1B transfers.

The role pays a top-of-market base plus competitive equity. The team is moving quickly with this hire. If you're interested in owning the intelligence behind an autonomous growth engine spending real money every day, apply now or send your CV directly to [email protected].