A little about myself

I’m Nikash, I’m a Software Engineer at Scale. I joined in August 2021 on the mapping team and am now working on content understanding. 

I graduated from the University of Virginia in May 2021, where I studied computer science and cognitive science. Before graduating, I had previously interned in biotechnology at Benchling, autonomous vehicles at Uber ATG, and fintech at Capital One. 

A fun fact about me is that I love Cuban food! Guava cheese pastries, cafe con leche, Cuban sandwiches, fried plantains…you name it. Check out Portos in Los Angeles or Colada Shop in DC if you ever get the chance.

Why Scale

Scale has been on my radar since 2019 when I was interning in the self-driving space. After finding Scale on a list of top YC alumni, I started reading more about the work they do with autonomous vehicle companies and other major tech players. I was especially fascinated by Scale’s light-speed growth and impressive customer list.

Out of college, I knew I wanted to work at a relatively smaller company where my work would have incredible impact. My good friend Rashid was already working at Scale and told me about the super cool projects he was working on. I was deciding between a few similarly-sized startups and ultimately chose Scale because of the breadth of industries they work in; from autonomous vehicles to social media leaders and much more. 

My experience on the Mapping team

I started Scale on the sensor fusion team where I worked on mapping for self driving cars. Autonomous vehicles rely on high-definition maps for perception, localization, and motion planning. Think of mapping as 2.5-dimensional labeling. AV customers send us LiDAR point clouds, which are collections of points representing scenes in the 3D space. We pre-process these point clouds and flatten them into a 2D or “top-down” view while preserving information like height. Then, we can draw road features like lane lines and traffic lights on this “top-down” view while being able to project them back into the 3D space. 

While on the mapping team, my first project was improving the quality of the maps we built, using computational geometry linters to validate map features. With these linters, I built a series of autofixes or autochecks to serve as a human-in-the-loop automated solution to programmatically fix quality issues of maps. This was super engaging and technically challenging work; I found myself using trigonometry and graph theory concepts I learned at school directly in the code I was writing! My manager even once recommended I read a computational geometry textbook he studied in order to solve a particularly difficult problem I was facing. It’s definitely quite rare to apply advanced math concepts from academia at work, and so I loved that this was my first main workstream at Scale.

I also primarily worked on algorithmically annotating semantic or “derived” zones of roads. Historically on our team, we focused on labeling observable features or pseudo-observable features on the map. That said, we knew our customers were having lots of trouble using these observable features to derive semantic regions and so we took a stab at solving this internally. These “derived” regions could include lanes, intersection areas, and other regions that are algorithmically developed but are based on visible road features. Ultimately, our proposal anticipated a massive pain-point that our customer had which led them to require these derived annotations in the maps we built. At Scale, we serve as “thought leaders” and technical partners for our customers, anticipating and solving their hardest open-ended challenges.

My experience on the Content Understanding team

In April, our leadership reached out to me asking if I’d like to participate in a new 6-month rotational engineering program called “Nighthawks”. As a part of the group, I’d build out new products from 0 to 1 and tackle the most critical and high-impact customer projects. I joined the product incubation and content understanding team, and since joining I’ve owned critical pilots with demanding timelines for a range of fascinating clients, including social media platforms and an NFT marketplace. On these projects, I’ve analyzed trends in social media and worked in detecting fraud, trust and safety issues.

Easily the most interesting aspect of the Nighthawks program has been participating in Go-to-Market, and learning how to interact with prospective customers. Participating in conversations with our sales teams, I’ve learned just how tactical and strategic Scale is when landing major deals, and I’ve observed a side of B2B that I hadn’t been exposed to before. Through Nighthawks, I’ve had the chance to demonstrate Scale’s offerings directly to many of these clients, which has taught me a ton about customer-oriented engineering. 

Life at Scale

Going into Scale, I had participated in a few internships where I built relatively siloed products, but I had never experienced true customer interactions and owning outcomes. At Scale, one’s responsibilities extend far beyond those of a vanilla engineer. One of our credos is “ownership is the job”; to succeed in delivering an outcome you’re required to participate in product-oriented discussions, be embedded in operations, and communicate directly with customers. The life and work of a Scale engineer is far more diverse than any other role I’ve been in prior to joining, which contributes to a vibrant and exciting work experience.