Staff Software Engineer, ML Infrastructure full_time

Hi, we’re The Browser Company 👋 and we’re building a better way to use the internet.

Browsers are unique in that they are one of the only pieces of software that you share with your parents as well as your kids. Which makes sense, they’re our doorway to the most important things — through them we socialize with loved ones, work on our passion projects, and explore our curiosities. But on their own, they don’t actually do a whole lot, they’re kind of just there. They don’t help us organize our messy lives or make it easier to compose our ideas. We believe that the browser could do so much more — it can empower and support the amazing things we do on the internet. That’s why we’re building one: a browser that can help us grow, create, and stay curious.

To accomplish this lofty task, we’re building a diverse team of people from different backgrounds and experiences. This isn’t optional, it’s crucial to our mission, as we need a wide range of perspectives to challenge our assumptions and shape our browser through a bold, creative lens. With that in mind, we especially encourage women, people of color, and others from historically marginalized groups to apply.

Browsers know everything about us and what we do everyday, yet they can’t predict our next move, morph themselves to better suit our tasks, or proactively reduce repetitive tasks during your work day. As a Machine Learning Engineer at The Browser Company, you’ll be working alongside product engineers, designers, and our Co-Founder, Hursh Agrawal, to build the next LLM-powered interface for the internet. You’ll be working to improve our on-device models so that our Members are able to get answers fast and take the busy work out of their days.

• Scope and spearhead projects to fine-tune, distill, or train transformer models for various features within the browser

• Build and maintain our on-device model architecture in MLX, ONNX, and other frameworks and model formats

• Trial and improve new on-device models to be performant on a variety of machines

• Build infrastructure to collect or generate training data for building or improving models in a privacy safe way

• Create ways for us to determine and track model performance and accuracy to improve our app efficiency overtime

• Onboard to the team and codebase with your onboarding buddy

• Attend a number of onboarding presentations on the company, product, codebase, and culture

• Get familiar with the Swift language, the Arc codebase, and how we ship features

• Ship a few bug fixes and small improvements across our codebase and tooling

• Have pair programmed with a few people on the engineering team

• Be regularly posting product feedback about the browser in our #dogfooding channel

• Be familiar with how we prototype and build new features, working with product engineers to brainstorm ways to use models to add intelligence to Arc

• Be familiar with our cloud infrastructure and data pipelines

• Be familiar with how we run inference both on-device and in the cloud

• Be testing new prototypes with existing, on-device models to test performance and viability

• Participate in product brainstorms to think about the future of Arc

• Be interview trained and interviewing candidates for roles at the Browser Company

• Be contributing to on-call rotations and jumping into incidents to support the team.

• Regularly attend weekly engineering discussions about our architecture, how we do code review, code style, and more

• Collaborate with our CTO and other ML and infrastructure engineers to shape the product roadmap

• Creatively solve problems with product engineers, using pragmatic solutions ranging from basic heuristics, regressions, ML models, to AI depending on the feature

• Own our on-device model architecture, updating it to try new models, change how we work with LoRA adapters, and optimizing it for performance and quality

• Drive projects from conception to production launch independently

• Own our infrastructure to collect training data and fine-tune models for our use-cases

• Have built out mechanisms to assess quality and performance, and be working with product teams to improve the efficacy of our models and heuristics

• Be mentoring and pair-programming with newer engineers to help them get spun up on the codebase

• 5+ years of experience optimizing and productionizing modern machine learning models, especially ones that run in a real-world product environment (bonus if you’ve worked closely with transformer models)

• You have production experience with a modern coding language like Python

• You have experience with fine-tuning, distilling, and improving modern machine learning infrastructure and models

• You’re passionate about performance and efficiency and coming up with creative approaches to building a new kind of browser

• You have experience independently running critical projects or initiatives with minimal guidance

• You’re pragmatic, motivated by nebulous problems, and excited to work in a startup environment with quick product validation cycles.

• We’re primarily focused on hiring in North American time zones and require that folks have 4+ hours of overlap time with team members in Eastern Time Zone.

💰 With our flexible compensation model, employees have the ability to choose the cash-to-equity ratio that best suits their individual needs. Every offer we extend includes three options: a salary-optimized offer, an equity-optimized offer, and a balanced offer.

The annual salary range for this role is $225,000-275,000 USD. The actual salary range offered will vary based on experience level and interview performance.

🧘🏻‍♀️ In addition to a competitive salary and equity package, we provide every employee with the following benefits:

• comprehensive benefits package with employee medical, dental, and vision – we cover 100% of premiums for employees, and up to 95% for dependents

• 401k plan

• flexible vacation policy – on average, our team members take between 15-20 vacation days a year, plus federal holidays (holidays vary by location)

• remote-friendly working environment – our core working hours are 11 AM-2 PM Eastern Time

• 12 weeks of paid parental leave

• $1,500 USD home office stipend

• Employees based in the US also receive additional services like free annual memberships to One Medical (where available), Talkspace, Teladoc, and HealthAdvocate

The Browser Company is a well-funded, ambitious startup of about 85 people (and growing!) who are passionate about building great products. We are a remote-first, distributed team, with the option to work in office in New York. We strongly support diversity and encourage people from all backgrounds to apply. 

🚙 To read more about what we value as a company, check out Notes on Roadtrips on our blog.