As Nikhil Harithas, Machine Learning Engineer at Patreon, shares his experience of moving from software engineer to ML engineer, he emphasizes the importance of balancing speed with scalability in building an ML platform. He advises focusing on providing value early on, as fast as possible, and being willing to iterate quickly. When deciding whether to build or buy, Nikhil suggests considering if the problem is unique to the company, and prioritizing building solutions that provide the most value for the business or product. He also highlights the importance of reducing manual work and measuring problems better through a value-based prioritization framework. With his experience in operationalizing machine learning systems, Nikhil stresses the need to consider data collection, training, deployment, monitoring, and retraining when deploying models. When hiring next, he recommends prioritizing people with horizontal skill sets who can tackle various parts of the problem end-to-end. Ultimately, Nikhil believes that ML can be done at smaller companies with the right mentality, tools, and people, offering opportunities for increased ownership and direct impact on performance.