Senior AI Engineer, Paper

• 5+ years building and deploying production AI/ML systems
• Hands-on experience operationalizing LLM-based systems (RAG, agents, prompt workflows, fine-tuning)
• Experience with multimodal or vision systems
• Demonstrated ownership of AI systems in production (monitoring, evaluation, iteration)
• Strong Python proficiency and experience with PyTorch or TensorFlow
• Experience working with distributed/cloud infrastructure for ML workloads

Desirable

• We are seeking a Senior AI Engineer to architect and operationalize multimodal AI systems at production scale
• You will own end-to-end AI initiatives—from research and experimentation through deployment and continuous optimization—powering AI features used by millions of learners
• This is a high-impact role with significant technical ownership in defining how AI is embedded into our platform
• Design and deploy real-time voice and vision AI systems for classroom environments
• Evaluate tradeoffs between fine-tuning, RAG pipelines, prompt-based approaches, and tool-using agents
• Build scalable inference systems with strict latency and cost constraints
• Fine-tune and evaluate LLMs, ASR models, and vision/multimodal architectures
• Design robust evaluation frameworks (offline + online)
• Implement safety guardrails and bias mitigation strategies
• Own the full ML lifecycle: data ingestion, training, validation, deployment, monitoring, and iteration
• Optimize infrastructure for GPU utilization, latency, and cost efficiency
• Partner with MLOps to build reliable, versioned AI pipelines
• Work closely with Product and Engineering to translate classroom needs into production-ready AI systems
• Clearly communicate tradeoffs between model complexity, performance, and cost
• Contribute to long-term AI roadmap and architecture decisions