Hi, we're The Browser Company đ 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 â through them we socialize with loved ones, work on our passion projects, and explore our curiosities. But on their own, they donât actually do a whole lot, theyâre kind of just there. They donât help us organize our messy lives or make it easier to compose our ideas. We believe that the browser could do so much more â it can empower and support the amazing things we do on the internet. Thatâs why weâre building one: a browser that can help us grow, create, and stay curious.
To accomplish this lofty task, weâre building a diverse team of people from different backgrounds and experiences. This isnât optional, itâs 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 canât 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, youâll be working alongside product engineers, designers, and our Co-Founder, Hursh Agrawal, to build the next LLM-powered interface for the internet. Youâll 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
Innovate our on-device model architecture in MLX, ONNX, and other frameworks and model formats
Trial and improve new on-device models, including fine-tuning new LLMs, 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
8+ years of experience optimizing and productionizing modern machine learning models, especially ones that run in a real-world product environment (bonus if youâve 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
Youâre pragmatic, motivated by nebulous problems, and excited to work in a startup environment with quick product validation cycles.
Weâre 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.
đ° 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 $250,000 - $300,000 USD. The actual salary range offered will vary based on experience level and interview performance.
đ§đ»ââïž 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.Â
đ To read more about what we value as a company, check out Notes on Roadtrips on our blog.
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Join The Browser Company as a Machine Learning Engineer, Tech Lead, where we are dedicated to revolutionizing the way you interact with the internet. Our team is on a mission to build a browser that goes beyond just a tool â we aim to create an experience that helps you organize your life, fosters creativity, and ignites curiosity. As a pivotal member of our engineering team, you'll collaborate with talented product engineers and designers to design the next LLM-powered interface. Imagine being at the forefront of improving on-device models that empower our Members to save time and effort by reducing repetitive tasks. Your core responsibilities will include scoping projects to enhance transformer models and refining our architecture using advanced ML frameworks. You'll build infrastructure to securely collect training data and assess model performance, influencing the future of our cutting-edge product. By joining us, you'll be part of a diverse, inclusive team that values a variety of perspectives. We welcome applicants from all backgrounds, particularly women and people of color. If you're excited about tackling unique challenges and thriving in a dynamic startup environment, The Browser Company could be your next adventure. Together, we can redefine what a browser can do for millions worldwide!
The web browser is one of the most important tools we use â not just on our computers, but in our lives. The world has changed in the past 15 years, but our web browsers look and behave pretty much th...e same. We think itâs time to push the web b...
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