AI Engineer – Machine Learning & Campaign Decision Engine
Own the intelligence layer of an AI-native growth engine startup's Learn Engine, driving autonomous decision-making for digital ad campaign management across platforms like Meta, Google, TikTok, and Snapchat. Build recommendation and scoring systems, design learning loops, write optimization policies for noisy live data, and orchestrate multiple agents to improve campaign strategies and return on ad spend. Requires 3+ years of experience in AI/machine learning, proficiency in Python, and familiarity with reinforcement learning and recommendation systems; offers $200K–$300K base plus equity in San Francisco.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
About the job
This role is being recruited by CoffeeSpace on behalf of an anonymous AI-native growth engine startup that replaces the entire media buying stack with autonomous digital workers for marketing teams.
We’re identifying a small number of exceptional AI engineers from our network. If there’s a strong fit, we’ll introduce you directly to the founding team.
Location: San Francisco, California, United States
Compensation: $200K–$300K base + competitive equity
Employment type: Full-time
Visa: Open to visa transfers only
About the company
This company develops an AI-native growth engine that autonomously manages digital marketing campaigns across platforms like Meta, Google, TikTok, and Snapchat. It serves industries such as mobile, gaming, AI, and tech, focusing on optimizing ad spend and campaign strategies.
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Founded in 2023, the company has secured $10M in funding and operates with a team of around 20 people across four offices on three continents. The team is led by technical founders who are directly involved in the development process.
About the role
You will own the intelligence layer of the company's Learn Engine, focusing on decision-making for campaign management. Your work will involve building recommendation and scoring systems, designing learning loops, and writing optimization policies. You will orchestrate multiple agents to improve campaign strategies over time.
What You’ll Do
- Build and refine the decision engine for campaign management.
- Design learning loops to enhance strategy over time.
- Develop optimization policies for noisy live data.
- Coordinate how multiple agents work together and evaluate outcomes.
- Be accountable for decision quality and return on ad spend.
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Why This Role Is Compelling
- You will have full autonomy and ownership over your work.
- Direct mentorship from the founders, with a flat team structure.
- Opportunity to work on live ad spend campaigns with immediate feedback.
- Competitive compensation and equity, with potential visa sponsorship.
The Ideal Candidate
- 3+ years of experience in AI, machine learning, or related fields.
- Proficient in Python and familiar with reinforcement learning and recommendation systems.
- Experience with ad optimization and bid management systems.
- Comfortable with designing strategies and working with live data.
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Next steps
- Apply via this LinkedIn job post
- We’ll review and reach out if there’s a strong match
- If aligned, we’ll introduce you directly to the team
- If this role isn’t the right fit, we may suggest and make introductions to other high-signal startup roles we’re recruiting for, always with your permission.
A quick note on authenticity
This is a real, active role that CoffeeSpace is recruiting for in close partnership with the hiring team. We don’t post speculative roles and work directly with teams on their actual hiring needs.
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