ML Software Engineer: Build Scalable AI Systems

Meta; San Francisco (CA); On-site; USD 183,997 - 257,000; Full time

Job summary

Meta in San Francisco is seeking experienced ML-focused Software Engineers to build scalable AI-driven features across mobile and web platforms. You’ll collaborate with product-design-ops to deliver high-impact experiences and mentor peers on complex projects.

Join a world-class team advancing responsible AI practices, optimize performance, and drive measurable improvements through data-driven decisions, with competitive compensation and equity opportunities.

Qualifications

• Experience driving change within an organization and leading complex technical projects.
• Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.

Responsibilities

• Collaborate with cross-functional teams to build innovative application experiences.
• Implement custom user interfaces using latest programming techniques and technologies.
• Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews.
• Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members.
• Architect efficient and scalable systems that drive complex applications.
• Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt.
• Work on a variety of coding languages and technologies.
• Establish ownership of components, features, or systems with expert end-to-end understanding.

Skills

Leadership

Data analysis

Communication

Tools

TensorFlow

PyTorch

Scikit-learn

NLP

Job description

Meta in San Francisco is seeking experienced ML-focused Software Engineers to build scalable AI-driven features across mobile and web platforms. You’ll collaborate with product-design-ops to deliver high-impact experiences and mentor peers on complex projects.

Join a world-class team advancing responsible AI practices, optimize performance, and drive measurable improvements through data-driven decisions, with competitive compensation and equity opportunities.