The Browser Company is building a better way to use the internet by creating a browser that can help users grow, create, and stay curious. They aim to leverage ML and AI to turn browser context into high-utility experiences that feel personal and improve over time, addressing the current limitations of browsers not actively assisting users.
Requirements
- 6+ years of experience training, 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)
- 3+ years mentoring and leading senior engineers with a track record of tech-leading critical work and setting a sustainable execution pace.
- You have production experience with Python and have experience fine-tuning open-source LLMs and going beyond simple LoRA fine-tuning
- Swift for on-device inference
- Python for models and tooling
- Experience with transformer models
- Experience fine-tuning open-source LLMs
Responsibilities
- Define and build our ML strategy, sequencing bets that improve Dia’s assistant and measurable user outcomes.
- Prototype, architect, and ship LLM‑powered features; establish techniques to train models that improve over time and personalize experiences, partnering with Design and Product Engineering to balance quality, speed, and scale for real‑world use.
- Audit and evolve the ML stack and infrastructure - spanning Swift for on-device inference and Python for models and tooling - to support both encoder and decoder model families across client and server.
- Partner on privacy and security by working with Security and Infra on data stewardship, deployment strategies, and responsible scaling.
- Establish ML Developer Experience by building tooling and workflows for high quality data curation, experimentation (fine-tuning, RL, prompting), evals, and continuous training to improve the models that power Dia.
- Support and build a talented team of machine learning engineers, helping them grow both technically and with a product mindset through fast iteration cycles.
- Own processes, recruiting, and onboarding—and proactively improve architecture and practices to enhance performance, stability, and maintainability.
Other
- Founding ML Engineering Manager
- Hands-on technical leaders who build high-performing and psychologically-safe teams with a diverse group of individuals.
- You’ll work closely with your team to make product decisions, prioritize work, ship features, and promote an engineering culture of knowledge sharing and mentorship.
- 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.
