Staff Machine Learning Engineer, Mozilla

• 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

Desirable

• A Staff Engineer is the next level from a Senior Engineer. At Mozilla this role can vary but typically a Staff Engineer is a domain expert who leads others within a single team to tackle multi-month projects
• Tasks that may be initially ambiguous or require significant planning and require them to influence or direct the work of several engineers
• They sequence deliverables and manage risks in their team's projects, provide feedback on our strategy and goals affecting the team, and turn our strategy into action for their team members
• Staff Engineers mentor others by stewarding some responsibilities to more junior and senior engineers so they can take on new ones. They collaborate with management on building team consensus and providing direction
• Staff Engineers identify gaps and opportunities for improvement to enable a culture of inclusion and allyship, at all levels of the organization
• 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