Fastino Labs

• Ship full-stack features end-to-end, owning the full lifecycle from conception to production with minimal oversight. • Build and maintain the infrastructure powering Fastino's services, keeping systems reliable and performant as we scale. • Work directly with AI researchers to bring new model capabilities into the product, moving fast without sacrificing quality. • Translate user feedback into product improvements, closing the loop quickly between what customers experience and what gets shipped. • Collaborate daily with the full team to review progress, surface blockers, and keep velocity high.

• Innovate at the edge of efficiency by designing and deploying high-performance agentic systems that leverage Fastino’s optimized model architectures to outperform traditional LLM benchmarks. • Bridge the gap between research and production by collaborating with engineering teams to turn novel architectural breakthroughs into scalable, low-latency solutions for enterprise customers. • Drive rapid, iterative prototyping of AI functionalities, refining model performance and task-accuracy based on real-world telemetry to ensure specialized models meet rigorous developer standards. • Own the stability and throughput of inference pipelines, proactively solving scalability bottlenecks to ensure models deliver consistent, reliable performance under massive operational loads. • Architect large-scale data and fine-tuning strategies to continuously improve the precision and domain-specific reliability of the Fastino models.

• Design, build, and deploy the critical small language models that are foundational to Fastino’s product • Own the full lifecycle of state of the art models, from prototyping and data analysis to deployment, monitoring, and the continuous improvement of models in production • Drive the data strategy to continuously improve model performance by analyzing distribution gaps, contributing to synthetic data pipelines, and creating automated annotation systems • Experiment with novel language model architectures, helping drive and execute Fastino's research roadmap • Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards • Build robust and real-world motivated evaluations • Partner with Fastino engineering team to ship model updates directly to customers • Establish best practices for code health and documentation on the team, to facilitate collaboration and reliable development

• Experiment with novel language model architectures, helping drive and execute Fastino's research roadmap • Optimize Fastino’s multimodal models to improve response quality, instruction adherence, and overall performance metrics • Architect data processing pipelines, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories • Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards • Build robust and real-world motivated evaluations • Partner with Fastino engineering team to ship model updates directly to customers • Establish best practices for code health and documentation on the team, to facilitate collaboration and reliable development