Requirements

6+ years experience as a Machine Learning engineer building tooling and services for machine learning applications in production.
Experience with designing and building machine learning tooling and infrastructure for training, deploying, inference, and validation of models.
Experience with distributed systems and platforms for AI integrations across a breadth of applications such as LLM APIs, Cloud-based, and open-source tooling.
Leading architecture designs to execution independently and track record of improving the team’s overall AI development velocity.
Strong problem-solving skills and ability to communicate complex concepts to technical and non-technical stakeholders.
Experience working collaboratively with product managers, project managers, and/or other non-engineering teams.
Effective documentation and communication skills on a distributed team.
Commitment to our values:
- Welcoming differences
- Being relationship-minded
- Practicing responsible participation
- Having grit

Nice to Haves

Knowledge of and experience with using LLM solutions across different cloud providers
You have previously successfully contributed to an open-source project.
Track record of not only building one, but multiple projects deployed with an active user base.
Experience with responsible AI, transparent algorithms, and putting users’ needs first.
Excellent communication skills, both in written and presentation form. You have the ability to quickly distill sophisticated topics into concepts that are tailored for your target audience.
You are a lifelong learner and continue to refine and improve your skills when you see an opportunity to do so.
Experience with the browser extensions architecture or ecosystem.
Experience working in open-source environments.

Lead the design, development, and integration of Generative AI solutions in Firefox, collaborating cross-functionally with product management, full-stack engineering, and design.
Build infrastructure for training and inference of LLMs and small language and vision models for use cases on the web and mobile Firefox product experiences.
Implement robust validation and testing procedures to ensure the developed models' generalizability and reliability
Continuously monitor and optimize deployed models for performance and efficiency

Generous performance-based bonus plans to all eligible employees - we share in our success as one team
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
Quarterly all-company wellness days where everyone takes a pause together
Country-specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program
Other benefits (life/AD&D, disability, EAP, etc. - varies by country)