{"id":415158,"url":"https://alion.io/job/hellyeah-ai-ai-engineer-learn-engine-intelligence-optimization","title":"AI Engineer — Learn Engine: Intelligence & Optimization","company":{"id":456128,"name":"Hellyeah AI","domain":"hellyeahai.com","url":"https://alion.io/company/hellyeah-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","Shanghai, China"],"countries":["US","CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":1000000,"currency":"USD","period":"year","gross":null,"usd_annual":1000000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Mastra","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-08-12T07:57:18Z","employer_posted_date":"2026-08-12","last_verified_at":"2026-10-30T13:35:39Z","board_verified":true,"closed_at":null,"days_open":79,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":79},"description":"Build the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat - every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools, you create the decisions. Together you build something nobody else has.\nMust Have:\nHas built recommendation, optimization, or decision systems where outputs improve future inputs.\nStrong statistical reasoning and experimentation judgment under noisy real-world data.\n\nStrong LLM orchestration or agent-system experience for reasoning over campaign context.\n\nCan design optimization policies, scoring systems, or automated recommendation loops.\n\nAI-first development workflow and ability to ship production systems quickly.\n\nNice to Have:\nAd-tech optimization patterns (bid management, budget allocation, ROAS optimization)\nReinforcement learning (RL) experience is a plus\n\nHyperparameter optimization (HPO) experience is a plus\n\nModel fine-tuning experience is a plus\n\nExperience building agent-driven automation (LLM agents that take actions)\n\nBackground in growth engineering, performance marketing, or data science\n\nExperience with Mastra or similar agent orchestration framework\n\nOwn the intelligence and optimization layer of Learn Engine. \nBuild recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. \nTurn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. \nDefine how the system learns from outcomes and continuously improves campaign strategy over time. \nThis role owns decision quality, optimization policy, and learning loops - 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