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Principal Machine Learning Engineer (LLMs)

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.

About The Role

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. At The Browser Company, we’re changing that by building Dia.

As a Principal Machine Learning Engineer, you’ll be working alongside product engineers, designers, and our cofounder and CTO, Hursh Agrawal, to build the next LLM-powered interface for the internet. You’ll collect datasets and build evals, fine-tune LLMs and smaller transformers like BERT, and iterate on our how we host models both in the cloud and on-device to improve latency and resource usage.

Overall you will...

  • Fine-tune, distill, and optimize LLMs to improve performance, reduce latency, and enhance efficiency for on-device and cloud-based inference.

  • Improve our on-device model architecture, leveraging frameworks like MLX, ONNX, and TFLite to ensure models run efficiently across different devices.

  • Experiment with and integrate new LLMs, fine-tuning them for specific browser-based use cases while balancing quality, speed, and resource constraints.

  • Build evaluation pipelines to track model performance, accuracy, and real-world effectiveness over time.

  • Collaborate with product ops teams to build and improve datasets that accurately match product needs.

  • Collaborate with product engineers and designers to prototype and ship AI-powered features that enhance user experience.

  • Optimize inference strategies, including running models on-device, in the cloud, or in hybrid configurations to maximize throughput and resource usage.

After 1 month you will...

  • Onboard to the team and codebase with your onboarding buddy

  • Attend onboarding presentations about the company, product, codebase, and culture

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

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

  • Have trained your first model, either improving an existing flow or enabling an entirely new one

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

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

After 3 months you will...

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

  • 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 Dia

  • Be trained to interview 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

After 6 months you will...

  • 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

  • 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

  • Drive projects from conception to production launch independently

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

Qualifications

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

  • You have deep experience fine-tuning open-source LLMs and going beyond simple LoRA fine-tuning

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

  • You're passionate about on-device performance and excited to push the boundaries of what's possible in a browser

  • You have experience independently running critical projects, shipping ML features, and leading 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.

Compensation and Benefits

💰 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 - $330,000 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 close to 100 people (and growing!) who are passionate about building great products. We are a remote-first, distributed team, with the option to work from office in Brooklyn, 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.

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What You Should Know About Principal Machine Learning Engineer (LLMs), The Browser Company

Hey there! We're thrilled you're interested in the Principal Machine Learning Engineer position at The Browser Company. We're on an exciting journey to reinvent how we use the internet, and we believe you could play a crucial role in shaping that vision. The internet is our daily companion, and it should do a lot more for us than just display content. With your expertise in machine learning, especially in fine-tuning large language models and other transformers, you’ll be working closely with our talented team, including our cofounder and CTO, to create innovative features that enhance our browsing experience. Imagine building an AI-powered browser that not only knows what you need but also anticipates your next move! You’ll be responsible for developing and optimizing machine learning models for both on-device and cloud environments, which means you’ll get to experiment with cutting-edge technologies and methodologies. You’ll also collaborate across teams to gather and enhance datasets, continuously iterating on model performance and efficiency. The Browser Company is deeply committed to diversity, innovation, and creativity, and we encourage applicants from all walks of life. If you're passionate about pushing the limits of what's possible in a browser and have the skills to back it up, we want to meet you! Together, we can build a better way to explore the web. Let’s make the browsing experience personal, efficient, and engaging!

Frequently Asked Questions (FAQs) for Principal Machine Learning Engineer (LLMs) Role at The Browser Company
What are the key responsibilities of a Principal Machine Learning Engineer at The Browser Company?

As a Principal Machine Learning Engineer at The Browser Company, your key responsibilities will include fine-tuning and optimizing large language models (LLMs) for better performance and efficiency both on-device and in the cloud. You’ll collaborate with product teams to create innovative AI-powered features, build evaluation pipelines for tracking model effectiveness, and work on improving our model architecture to meet the demands of real-world applications.

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What qualifications do I need to apply for the Principal Machine Learning Engineer position at The Browser Company?

To apply for the Principal Machine Learning Engineer position at The Browser Company, you should have at least 8 years of experience in optimizing and deploying machine learning models, particularly in environments where they impact real-world user experiences. Familiarity with transformer models, open-source LLMs, and experience in programming with languages like Python are crucial. You should also demonstrate your ability to lead initiatives and tackle complex problems independently.

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How does The Browser Company support innovation in the role of a Principal Machine Learning Engineer?

The Browser Company fosters innovation by giving you the autonomy to experiment and integrate new LLMs tailored for browser-specific use cases. You'll have the opportunity to work alongside a dynamic team and collaborate effectively in building cutting-edge features while receiving support from the cofounders and seasoned professionals. Our team thrives on creativity and is committed to continuous improvement, allowing you to test new ideas and methodologies.

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What is the company culture like at The Browser Company for a Principal Machine Learning Engineer?

At The Browser Company, the culture is inclusive, collaborative, and forward-thinking. As a Principal Machine Learning Engineer, you'll be surrounded by diverse talent who shares a passion for redefining user experiences on the web. We strongly value individual perspectives, encouraging everyone to contribute ideas that challenge assumptions and foster creativity in our projects. You’ll find a supportive environment aiming for innovation and excellence.

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What are the growth opportunities at The Browser Company for this role?

Joining as a Principal Machine Learning Engineer at The Browser Company opens up numerous growth opportunities. Not only will you work on impactful projects impacting millions of users, but you'll also have a chance to mentor fellow engineers and shape the country's technology landscape. You'll continuously learn and adapt within a thriving startup environment, paving the way for professional advancement and innovation.

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Common Interview Questions for Principal Machine Learning Engineer (LLMs)
Can you describe how you've optimized LLMs for performance in the past?

When answering this question, highlight a specific project where you implemented techniques such as fine-tuning, distillation, or pruning to enhance LLM performance. Discuss the metrics you used to measure success and any challenges you faced, demonstrating your problem-solving skills and the impact your optimizations had on user experience.

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What strategies do you employ to evaluate machine learning models for real-world applications?

Discuss your approach to setting up evaluation pipelines that measure model performance over time. Detail how you assess accuracy, efficiency, and user satisfaction—mention any tools or methodologies you've used, along with examples of how these evaluations led to actionable insights for product improvements.

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How do you stay updated on the latest advancements in machine learning and AI?

Explain your methods for staying informed, such as reading research papers, attending conferences, participating in online courses, or being active in machine learning communities. Share specific examples of how you've applied recent innovations to previous projects to demonstrate your commitment to ongoing learning and mastery in the field.

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What experience do you have with on-device model implementation?

Provide examples of previous projects that involved implementing machine learning models on-device. Discuss the frameworks you've used, such as TensorFlow Lite or ONNX, and mention any performance optimizations you made to ensure efficient execution across various devices. This showcases your technical expertise and understanding of practical applications.

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Can you walk us through a time you led a critical ML project from conception to launch?

Use the STAR method (Situation, Task, Action, Result) to describe a past project where you took charge. Focus on your responsibilities, the challenges you encountered, the strategies you employed to overcome these obstacles, and the outcomes of your efforts. This conveys your leadership skills and ability to drive projects successfully.

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How do you approach collaboration with cross-functional teams?

In your answer, emphasize your communication style, adaptability, and willingness to listen to ideas from various team members. Provide an example of a successful project where cross-functional collaboration led to a positive outcome, which highlights your teamwork and relationship-building skills.

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What motivates you to work in a startup environment?

Discuss your passion for innovation and how you thrive in a dynamic setting. Highlight your excitement for quick product validation cycles, the opportunity to shape projects, and the chance to work closely with a diverse group of professionals. This demonstrates your alignment with The Browser Company's values and mission.

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What techniques do you use to ensure the quality of your machine learning models?

Detail your processes for implementing best practices in model training and evaluation, such as regular performance monitoring, user feedback integration, and continuous improvement cycles. Mention any tools or frameworks that assist in quality assurance and how these techniques impacted previous projects.

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How would you handle a project that isn't meeting its performance benchmarks?

Describe your problem-solving approach—initially gathering data to pinpoint the bottlenecks, experimenting with various optimization techniques, and collaborating with team members for insights. Sharing a specific example will further illustrate your methodical and proactive attitude toward overcoming challenges.

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What innovations do you foresee for machine learning in user-facing applications like web browsers?

Provide insights into emerging trends in machine learning that could significantly enhance user interactions, such as personalization using predictive models, more seamless voice interactions, or real-time content recommendations. Tie in how these innovations could be applicable specifically to The Browser Company's goals.

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The web browser is one of the most important tools we use — 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 it’s time to push the web b...

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Full-time, remote
DATE POSTED
March 22, 2025

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