Anish Shah is a machine learning practitioner whose career has been defined by a simple motivation: turning ML ideas into ML products. He started out working with multiple data science teams at SAP, where he gained hands-on experience across traditional machine learning, deep learning, and recommendation systems. That mix of techniques, from classic models to neural approaches, gave him an early appreciation for matching the right method to the right problem.

Today, Anish is at Weights & Biases, where he crafts ML projects that help better serve customers. His work sits at the intersection of applied machine learning and the tools teams rely on to run it well, and he takes particular satisfaction in the moments when a struggling project turns around, converting oh nos into ahas. Whether the challenge is framing an experiment, shaping a workflow, or making a model useful in the real world, he focuses on the practical steps that move work from notebook to production.

Beyond his day-to-day projects, Anish shares what he learns along the way, with a public Weights & Biases profile documenting his experiments. His combination of enterprise data science experience and product-focused ML engineering makes him a grounded voice for teams looking to ship machine learning that actually works.