Machine Learning Engineer, Tech Lead

Summary

Join The Browser Company and become a Machine Learning Engineer, working alongside a talented team to build the next LLM-powered interface for the internet. You will scope and spearhead projects to fine-tune and train transformer models, innovate on-device model architecture, and build infrastructure for data collection. The role involves improving on-device models for faster answers and reduced workload for users. You will collaborate with product engineers, designers, and the Co-Founder. This position requires 8+ years of experience optimizing and productionizing machine learning models, experience with modern coding languages, and a passion for performance and efficiency. The Browser Company offers a competitive salary, comprehensive benefits, flexible vacation, remote work options, and paid parental leave.

Requirements

• 8+ years of experience optimizing and productionizing modern machine learning models, especially ones that run in a real-world product environment (bonus if you’ve 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
• 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

• 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

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 - $300,000 USD . The actual salary range offered will vary based on experience level and interview performance
• 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