⚙️ Senior Machine Learning Engineer – Applied AI / Agent Systems
Company: AdsGency AI
📍 Location: Onsite (San Francisco City)
💼 Employment Type: Full-Time
🚚 Relocation to San Francisco City Required
🛂 We Sponsor OPT / CPT / STEM-OPT / DO NOT sponsor H1B Transfer
🚀 About AdsGency AI
We’re AdsGency AI — an AI-native startup building a multi-agent automation layer for digital advertising.
Our system uses LLM and ML-driven agents to autonomously launch, scale, and optimize ad campaigns across Google, Meta, TikTok, and more — no human marketer required.
Our mission: build the operating system where AI runs performance marketing better than humans ever could.
We’re backed by top-tier investors and moving fast. This is your chance to join early — and help design the ML foundation that powers the next evolution of ad intelligence.
🧠 The Role – Senior Machine Learning Engineer
As a Senior Machine Learning Engineer, you’ll design, train, and deploy AI models that drive AdsGency’s agent intelligence — from ad performance prediction to cross-channel optimization and creative generation.
You’ll bridge the gap between data science, engineering, and systems design, shaping the brain of our multi-agent OS.
This role sits at the core of AdsGency’s intelligence layer — where models don’t just predict, but act.
🔧 What You’ll Build
• 🧠 Agent Intelligence Models: Develop and fine-tune models that predict campaign performance, bid pacing, and creative success.
• 📊 Reinforcement & Decision Systems: Build RL and multi-objective optimization frameworks enabling agents to learn from feedback and improve autonomously.
• 🧬 LLM + ML Hybrid Systems: Integrate generative agents (OpenAI, Claude, LangGraph) with quantitative models for adaptive decision-making.
• ⚙️ Data Pipelines: Architect and maintain scalable feature pipelines and embeddings for multi-platform ad data.
• 🔍 Measurement & Attribution: Design models to unify performance signals across Google, Meta, TikTok, etc., handling delayed and biased feedback.
• 📈 Experimentation Frameworks: Develop A/B testing and counterfactual learning systems to validate model improvements.
• 🚀 ML Infrastructure: Own the training → evaluation → deployment lifecycle using modern MLOps practices (e.g., Weights & Biases, Airflow, Docker).
💻 Tech Stack
Modeling & ML: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, Hugging Face, Transformers
Languages: Python, Go (for systems), SQL
Infra & MLOps: AWS/GCP, Docker, Kubernetes, Airflow, Weights & Biases, MLflow
Data Systems: Kafka, PostgreSQL, Redis, Supabase, Qdrant/Weaviate (vector DBs)
AI Layer: OpenAI, Claude, LangChain, LangGraph, CrewAI
💡 What You Bring
✅ 4–8 years of experience in ML engineering or applied data science
✅ Strong foundation in ML algorithms, model lifecycle, and feature engineering
✅ Proficiency in Python and ML frameworks (PyTorch/TensorFlow)
✅ Experience building models that go into production, not just notebooks
✅ Understanding of distributed systems, data pipelines, and model serving
✅ Experience with A/B testing, reinforcement learning, or online learning
✅ Curiosity about how LLMs and agents can augment traditional ML systems
✅ Startup mindset — fast iteration, ownership, and bias for impact
🧩 Bonus Points
✨ Experience in AdTech / MarTech, especially prediction, attribution, or bidding systems
🧠 Experience integrating LLMs with structured data pipelines
⚙️ Knowledge of reinforcement learning, causal inference, or bandit algorithms
🌱 Prior work in early-stage or high-growth startups
🎯 Strong sense of product impact — you ship models that move metrics
💰 Why Join AdsGency AI?
• Competitive salary + meaningful equity
• Core ownership in a fast-scaling AI company
• Work directly with founders and research engineers on frontier agentic systems
• Culture of speed, autonomy, and craftsmanship — no corporate bureaucracy
• Build systems that redefine how advertising learns and optimizes itself
• Visa sponsorship (OPT / CPT / STEM-OPT / no H1B Transfer)
Industry: AI & Software Development
Employment Type: Full-Time
Location: Onsite (San Francisco City)
