Senior AI Developer

We’re looking for a Senior AI Engineer to design, build, and deliver production AI/ML systems. This role is ideal for an engineer with several years of experience who can confidently own features end-to-end, contribute to architectural decisions, and bring strong technical judgment to the problems they take on. In this role, you will work as a key contributor on a cross-functional team, designing and implementing models, building the data pipelines and training workflows around them, and deploying systems to production environments. You’ll be joining real, in-flight work where reliability, performance, and scalability matter. You’ll collaborate with experienced engineers to enhance existing systems, deliver new capabilities, and contribute to the technical decisions that shape how our AI work scales over time. Why This Role Matters At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate. Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on. What You’ll Do Craft & Delivery Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability Bring an AI-forward coding mindset to your daily work, using tools like Claude and Cursor to ship higher-quality work at pace Collaboration & Communication Partner closely with product, engineering, and data teams to align AI work with broader product and business goals Translate technical tradeoffs, model behavior, and constraints into terms non-specialists can act on Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback Leadership & Influence Contribute to AI architecture decisions with thoughtful perspective on tradeoffs and long-term implications Take ownership of meaningful work end-to-end, including the unglamorous parts of getting AI into production Raise the bar on engineering practices through your own work and by supporting more junior engineers when opportunities arise What You’ll Bring Required Turning raw data into training sets at tens-of-millions-of-documents scale, using PySpark, Hive and HDFS. This is the first responsibility listed. Large-scale batch LLM inference and production inference (vLLM, Amazon Bedrock batch). Large-scale distributed training, with SageMaker HyperPod named explicitly. LoRA/QLoRA fine-tuning and deep learning fundamentals. Reinforcement learning (GRPO or PPO style) for ranking and reasoning. The analysis calls this a named requirement, not a nice-to-have. Preferred Trainium / Neuron SDK. Ranking and reranking with real metrics (NDCG, Recall), ideally sequential or generative recommenders such as a travel recommender. Helpful Extras and Unique Skills You’ll Do Well Here if You Are A doer.