Machine Learning Engineer

Senior Machine Learning Engineer Applied AI / Agent Systems Company: AdsGency AI 🚚 Relocation to San Francisco City Required Were 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. Were 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. 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 Were 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. Were 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, youll design, train, and deploy AI models that drive AdsGencys agent intelligence from ad performance prediction to cross-channel optimization and creative generation. Youll 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 AdsGencys intelligence layer where models dont just predict, but act. What Youll Build Agent Intelligence Models: Develop and finetune models that predict campaign performance, bid pacing, and creative success. Reinforcement & Decision Systems: Build RL and multiobjective 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 decisionmaking. Data Pipelines: Architect and maintain scalable feature pipelines and embeddings for multiplatform 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, Scikitlearn, XGBoost, LightGBM, HuggingFace, 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 48 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 earlystage or highgrowth startups 🎯 Strong sense of product impact you ship models that move metrics Why Join AdsGency AI? Competitive salary + meaningful equity Core ownership in a fastscaling 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)#J-18808-Ljbffr