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Product Operations, AI

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

The Browser Company is hiring for Product Operations to help build the foundation for Dia, our browser-native AI assistant. This role is perfect for someone who loves turning complex user needs into structured training data and enjoys working at the intersection of AI and user experience.

You'll combine systematic thinking with meticulous attention to detail to create the datasets that help our models understand and assist users more effectively. Your work will be crucial to Dia's success, creating the training data that enables our AI to understand user intent and deliver helpful responses.

From evaluation sets to large-scale training data, you'll build the datasets that help us measure, improve, and scale our AI capabilities. This isn't just about data collection – it's about understanding our users deeply and translating their needs into examples that help our models learn and improve.

Overall you will...

  • Build high-quality datasets for model evaluation and training, from targeted eval sets to large-scale training data

  • Partner with engineers to ensure datasets are comprehensive, properly formatted, and easy to use

  • Work with product owners to understand product goals and translate them into effective training data

  • Collaborate with User Research and Membership teams to understand user needs deeply

  • Use support tickets and user feedback to inform and inspire dataset creation

  • Establish and maintain quality standards for our datasets

  • Navigate technical tools to manage and update training data

After 1 month you will...

  • Get onboarded onto the team with an onboarding buddy

  • Learn about our AI strategy and how datasets drive model improvements

  • Get familiar with our technical tools including Braintrust and GitHub

  • Begin contributing to evaluation datasets for specific features including labeling/annotation of existing sets

  • Start understanding patterns in user interactions with Dia

  • Regularly share feedback about Dia in our #dogfooding channel

After 3 months you will...

  • Independently create evaluation datasets for new features

  • Run evals yourself and in tandem with engineers, tracking scores over time

  • Regularly analyze user feedback to inform dataset creation

  • Develop systematic approaches to dataset organization

  • Learn to identify what makes a good training example

  • Start contributing to larger-scale dataset projects

After 6 months you will...

  • Own dataset creation for both evaluation and training purposes

  • Help define quality standards for dataset development

  • Work with product owners to align datasets with product vision

  • Create documentation and processes for dataset management

  • Build relationships across research and membership teams

  • Contribute insights about user patterns and model capabilities

Qualifications

  • You have 3+ years of hands-on experience with AI evaluation (”evals”), data labeling, or model fine-tuning. You have a strong understanding of best practices in these areas.

  • You have 5+ years of experience working with large datasets, from spreadsheets to user feedback, in a technical, product, or QA role.

  • You understand how users think about product capabilities, can distinguish between current features and future potential, and collaborate across teams to turn insights into action.

  • You're comfortable with technical tools like GitHub and can navigate engineering-adjacent systems (Sqlite, Python, Braintrust, or Xcode experience are a plus!)

  • You're excited about AI, language models, and taking creative approaches to dataset creation to ensure diverse, high-quality examples for AI training and evaluation.

  • 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 $140,000- $190,000 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 plus federal holidays (holidays vary by location)

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

  • 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.

Average salary estimate

$165000 / YEARLY (est.)
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$140000K
$190000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Product Operations, AI, The Browser Company

The Browser Company is on the lookout for a passionate Product Operations professional to join our delightful team and help us create Dia, our innovative browser-native AI assistant. If you thrive on transforming complex user needs into meticulously structured training data, this role is tailor-made for you! You’ll be the magic behind the scenes, working to ensure that our AI can truly understand its users and provide relevant, helpful responses. Your efforts in building high-quality datasets are essential for Dia’s capabilities, ranging from model evaluation to large-scale training. Imagine collaborating with engineers to ensure datasets are comprehensive and align with product goals, while also diving deep into user feedback and support tickets to inspire dataset creation. At The Browser Company, we’re a diverse team determined to build a better web experience, and we need someone like you to help us achieve that. You don’t just collect data—you’ll bring to life a deeper understanding of our users, directly impacting how they interact with AI. With an environment that values creativity, feedback, and team collaboration, you’re not just signing up for a job; you’re crafting a new reality in the world of web browsers. If you’re ready to contribute to something extraordinary and embody our values of inclusion and innovation, we’d love for you to apply!

Frequently Asked Questions (FAQs) for Product Operations, AI Role at The Browser Company
What are the responsibilities of a Product Operations professional at The Browser Company?

As a Product Operations professional at The Browser Company, your main responsibilities include building high-quality datasets for model evaluation and training, collaborating with engineers to ensure data integrity, and translating product goals into actionable training data. This role is integral to helping our AI assistant, Dia, understand user intent, and requires a thorough understanding of user needs, which you will gain from analyzing user feedback and support tickets.

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What qualifications are required for the Product Operations position at The Browser Company?

To be considered for the Product Operations role at The Browser Company, you should have over 3 years of experience with AI evaluation, data labeling, or model fine-tuning, along with 5+ years of experience handling large datasets in a technical or product role. Familiarity with technical tools such as GitHub and knowledge of systems like Sqlite or Python are advantageous, while a passion for AI and creative dataset development is essential.

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What is the expected career progression for a Product Operations member at The Browser Company?

In the Product Operations role at The Browser Company, you can expect a structured career progression. Initially, you'll get onboarded and learn about our AI strategy. Within three months, you’ll create evaluation datasets independently and contribute to larger projects. By the six-month mark, you’ll take on owning dataset creation and establishing quality standards, contributing significantly to Dia's capabilities.

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What does the work environment look like for the Product Operations role at The Browser Company?

The Browser Company fosters a remote-friendly working environment, with core working hours of 11 AM-2 PM Eastern Time. You’ll be part of a distributed team that emphasizes collaboration and inclusion, taking part in innovative projects without geographical constraints. Hence, you’ll enjoy a flexible vacation policy and a range of benefits that promote work-life balance.

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How does The Browser Company support diversity in the hiring process for Product Operations roles?

At The Browser Company, we prioritize building a diverse team and actively encourage applications from women, people of color, and historically marginalized groups for our Product Operations roles. We believe diversity is essential to our mission, providing unique perspectives that drive innovation and inform the development of our products.

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Common Interview Questions for Product Operations, AI
What strategies do you use to build quality datasets for AI training in the Product Operations role?

When answering this question, discuss how you analyze user feedback and support tickets, collaborate with product teams, and employ systematic approaches to dataset organization. Highlight your understanding of user intent and the importance of diversity in examples, demonstrating your commitment to high-quality dataset creation.

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How do you handle feedback from users about AI interactions?

To respond effectively, mention your approach of regularly analyzing user feedback and incorporating valuable insights into your dataset creation. Discuss how this informs your training data and aids in enhancing the AI's ability to provide relevant responses, showing the interviewers that you value user input and continuous improvement.

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Can you explain how you've previously collaborated with engineers on dataset creation?

Share specific examples of your past experiences where you partnered with engineers to ensure the datasets were comprehensive and properly formatted. Elaborate on how this collaboration contributed to the overall product development and enhanced the AI's performance in understanding user needs.

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What tools are you familiar with for managing and updating training data?

Be specific about your experience with tools like GitHub or any database systems like Sqlite and how you’ve utilized them in previous roles. Discuss how these tools helped streamline dataset management processes and improve data quality, showcasing your technical skills.

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What is your understanding of the relationship between product goals and dataset creation?

Emphasize how you've worked with product owners in past roles to translate product goals into effective training data. Discuss ways to align datasets with user experience objectives and how that impacts the AI's ability to meet user needs.

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How do you approach learning about user needs in your role?

Talk about using various resources like user feedback, support tickets, and collaboration with user research teams to gain insights into user needs. Discuss the importance of understanding these needs deeply for creating relevant datasets that enhance the AI’s utility.

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What methods do you use for evaluating large datasets?

Explain your approach to evaluating datasets, including any metrics you track over time, and how these evaluations inform the quality of the training data. Share relevant tools or frameworks that you’ve utilized in the evaluation process.

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Can you describe a challenging dataset project you've managed?

Provide a detailed description of a challenging project, outlining the obstacles faced, your approach to overcoming them, and the ultimate outcome. This shows your problem-solving skills and experience in handling complex datasets, relevant for the Product Operations role.

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Why are you interested in AI and the Product Operations position?

Share your passion for AI and its potential to revolutionize user experience. Relate your interests to The Browser Company’s mission to innovate web browsing, articulating how your values align with the company’s goals and your commitment to create meaningful datasets.

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What are your expectations for collaboration within a remote team?

Discuss the importance of communication, proactive engagement, and mutual support in a remote environment. Share examples from previous experiences where you effectively collaborated in remote settings, emphasizing your adaptability and commitment to team success.

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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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