Staff Machine Learning Engineer

Summary

Join The Browser Company and help build a better internet experience. As a Machine Learning Engineer, you will work with a team to build the next LLM-powered interface for the internet. You will fine-tune LLMs, optimize model architecture, integrate new LLMs, build evaluation pipelines, collaborate with product teams, and optimize inference strategies. The role requires 5+ years of experience optimizing and productionizing modern ML models, particularly those running in real-world product environments. The company offers a flexible compensation model with a salary range of $250,000-$300,000, comprehensive benefits, flexible vacation, remote work options, and paid parental leave. The Browser Company is a remote-first, distributed team with an office in Brooklyn, New York.

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
• 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
• 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
• 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