Top Hybrid Machine Learning Engineer Jobs in Los Angeles, CA

Design, build, and productionize causal ML models (uplift, heterogeneous treatment effects), analyze A/B tests and quasi-experiments, collaborate with product and engineering, ensure scalable, maintainable infrastructure, and balance model complexity with interpretability and business impact.

Lead and grow a team of ML and software engineers to build large-scale indexing, retrieval, and ranking systems for Snapchat ads. Define architecture and evaluation frameworks, collaborate with product and data science, measure outcomes, and raise engineering and ML standards while shaping Snap's broader ML strategy.

Lead analytics for M&A deals by building scalable data pipelines, applying ML and generative AI for due diligence and forecasting, automating reporting, visualizing insights, mentoring junior staff, and advising Private Equity clients to drive investment and portfolio value creation.

Lead research and applied science for personalization and recommender systems across Crunchyroll products. Define problems, build and evaluate models (ranking, retrieval, sequence, bandits, LLM-enabled approaches), design offline/online experiments, collaborate with product and engineering to productionize solutions, and establish best practices for experimentation, reproducibility, and model governance to improve discovery, engagement, and long-term user value.

Lead design and delivery of production-ready AI systems within the ION Factory OS, ship AI-driven and core product features, architect scalable cloud-native systems and ML pipelines, implement RAG and MCP integrations, collaborate with product and data teams, ensure reliability and scalability, and mentor junior engineers.

Design and build ETL pipelines and data integrations, develop LLM-powered RAG systems and AI Agents, manage vector databases, run evaluations and fine-tuning, apply ML for recommendations and analytics, ensure data quality and A/B testing to drive product decisions.

The Machine Learning Engineer II at Tinder will develop and deploy machine learning models to enhance user experiences, collaborate with cross-functional teams, and analyze model impact through experiments.

Own and ship full-stack features across frontend, backend, and data layers. Extend a Brand Knowledge Graph in Neo4j, build predictive optimization and measurement systems, design LLM orchestration and AI integrations to minimize calls, and deliver client-facing demos and QA. Translate complex data and models into actionable insights and maintain integrations and tracking infrastructure.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

Embed with clinical and operations teams to identify high-impact problems and build production AI systems. Design and deploy LLM/RAG-driven tools, data pipelines, APIs, models, and user-facing applications using messy clinical and claims data. Iterate quickly based on real-world feedback and operational needs.