Company: Gridlines is a rapidly growing financial modelling consultancy practice. We transforming the world of financial modelling, helping our clients to make complex financial decisions quickly and with confidence. We love to work with exciting clients that are making a big impact on the world around us, helping to tackle some of the world's greatest challenges. We plan to continue our rapid expansion and are looking for the brightest and best talent to join us on this journey. Role: We are seeking an experienced analyst that is passionate about financial modelling and driven by growth. You will work with a team of modelling professionals to create, analyse and optimise complex financial models, ensuring they are robust and reliable.

• You'll build the intelligence layer that powers that mission. That means working with 500M+ labeled blockchain addresses, training models on data no one else has, and shipping AI/ML systems that help real investors make better decisions and grow their portfolios. • Design and build AI/ML models on top of the richest onchain dataset in the world — then make them fast, scalable, and production-ready • Work shoulder-to-shoulder with engineers and product to ship models that actually reach users • Stay ahead of the curve in both AI/ML and blockchain — this space moves fast, and we need someone who moves faster • Level up the team: mentor junior engineers, raise the bar on what good looks like • Own your work end-to-end; from data pipeline to deployed feature

• Lead a broad portfolio of end-to-end initiatives in multimodal LLM and audio algorithms to achieve Netflix’s ambitious localization goals. • Mentor, support, and inspire a team of Research Scientists and Machine Learning Engineers. • Partner with technical leads on defining area strategy, planning and executing projects, and developing talent. • Set and operationalize a high bar for execution speed and quality. • Build strong relationships with cross-functional partners to shape long-term collaborations and shared visions. • Act as a functional leader and domain expert.

• Design and implement machine learning features used in production customer workflows. • Help identify and close feature and behavior gaps between our ML capabilities and common frameworks (e.g., Spark ML, scikit-learn). • Proactively evaluate semantic differences, defaults, and edge cases that could surprise customers. • Partner with product, architects, and customer-facing teams to anticipate upcoming customer needs and gaps. • Investigate and resolve issues where ML behavior diverges from user expectations (e.g., model output, metrics, configuration semantics). • Contribute to other ML initiatives including new models, metrics, performance improvements, and infrastructure work. • Analyze and improve the performance of existing ML code, balancing correctness and stability with customer facing latency. • Write clear design docs, tests, and documentation to make behavior explicit and prevent regressions.