Sr. Machine Learning Engineer

San Francisco, CA About the role A San Francisco startup is seeking a Senior Machine Learning Engineer to build and scale AI systems. You'll work on impactful projects with models used daily by many users, with your work directly influencing the product. Key Responsibilities Own ML projects end-to-end: research, prototyping, training, deployment, and iteration. Build multimodal ML systems for video, text, images, and audio data. Develop applications using Large Language Models (LLMs) and modern AI techniques such as Retrieval-Augmented Generation (RAG) with external AI APIs. Create models for content understanding and classification across text and visual media. Build search and discovery systems using semantic embeddings and retrieval methods. Develop audio analysis pipelines. Maintain and optimize MLOps infrastructure, including data pipelines, model serving, monitoring, and experiment tracking. Work with product teams and stakeholders to turn high-level requirements into deployable ML solutions. Requirements Have 4-8 years of ML engineering experience, including production model deployment. Be proficient in Python and core ML concepts, writing clean and maintainable code. Have experience building end-to-end ML pipelines: data handling, training, deployment, and monitoring. Be comfortable working with LLMs and AI APIs in production. Have expertise across NLP, computer vision, and audio processing. Be product-focused, identifying where ML can solve user problems and improve outcomes. Tech Skills Deep Learning: Neural networks, transformers, CNNs NLP / LLMs: RAG systems, prompt engineering, vector databases, fine-tuning, orchestration tools Computer Vision: Image classification, object detection, visual content understanding, embeddings Search & Retrieval: Semantic search, multimodal retrieval, embedding models MLOps: Model deployment, monitoring, experiment tracking (e.g., MLflow) Cloud ML: Deploying models on cloud platforms (AWS, GCP) with scalable inference Why This Role is Exciting Lead ML strategy and infrastructure in a growing startup environment. See your models reach users quickly for fast feedback and iteration. Work on challenging ML problems across video, language, and audio. Join an early ML team in a product-focused, engineering-first culture. Enjoy high autonomy and ownership over impactful projects. twenty80.io