Staff Machine Learning Engineer, Product

Summary

Join The Browser Company and help build Dia, the next LLM-powered interface for the internet. As a Machine Learning Engineer, you will collaborate with a diverse team to fine-tune LLMs, optimize on-device model architecture, and set product direction. You will improve model performance, reduce latency, build evaluation pipelines, and iterate on the product experience. The role involves working with various frameworks like MLX, ONNX, and TFLite, and staying up-to-date with the latest advancements in AI. You will also contribute to data collection and model fine-tuning for various use cases. This is a remote-friendly position with flexible working hours and a competitive compensation package.

Requirements

• 5+ 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

Responsibilities

• 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
• Set product direction via your expertise in ML and how it can help power Dia and increase it’s capabilities
• Keep up with the latest advancements in AI and apply new models and techniques to improve Dia where applicable
• Build evaluation pipelines to track model performance, accuracy, and real-world effectiveness over time. You'll also collaborate with product ops teams to build and improve datasets that accurately match product needs
• Iterate on the product experience by integrating and improving the models used in Dia, working alongside product engineers and designers
• Onboard to the team and codebase with your onboarding buddy
• Attend onboarding presentations about the company, product, codebase, and culture
• Become familiar with the Swift language, the Dia codebase, and how we ship features
• Ship a few bug fixes and small improvements across our product codebase and tooling
• Have trained your first model, either improving an existing flow or enabling an entirely new one and have integrated it yourself into our product codebase
• 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 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
• 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

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