Software Engineer, Machine Learning, Applied AI
Role Overview
Software Engineer in Meta’s Applied AI Engineering organization, working to improve frontier language models and AI products for real-world tasks.
The work includes identifying model capability gaps and building systems, agentic pipelines, reinforcement-learning environments, and evaluations that generate training signals.
The organization describes itself as a flat, AI-native group with broad scope, light processes, and fast decisions.
Key Skills for This Role
Full Job Posting
Role overview
Software Engineer in Meta’s Applied AI Engineering organization, working to improve frontier language models and AI products for real-world tasks.
The work includes identifying model capability gaps and building systems, agentic pipelines, reinforcement-learning environments, and evaluations that generate training signals.
The organization describes itself as a flat, AI-native group with broad scope, light processes, and fast decisions.
Responsibilities
- Collaborate with product, design, operations, and infrastructure teams to build application experiences and custom user interfaces.
- Analyze and optimize code for quality, efficiency, and performance, and provide feedback in code reviews.
- Set team direction, lead major initiatives, provide technical guidance and mentorship, and support onboarding.
- Architect scalable systems, resolve performance and scalability issues, and reduce technical debt.
- Own components, features, or systems end to end and work across coding languages and technologies.
Minimum qualifications
- Demonstrated experience driving organizational change and leading complex technical projects.
- Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.
Preferred qualifications
- Master’s degree or PhD in Computer Science or a related technical field; experience with TensorFlow, PyTorch, or Scikit-learn.
- Knowledge of information retrieval, data structures and algorithms, graph theory, optimization, or NLP techniques.
- Experience integrating AI tools into workflows; responsible AI practices; and ongoing development in prompt/context engineering or agent orchestration.
- Experience designing synthetic training-data or evaluation pipelines, or building training-data verification and quality controls.
- Ability to solve ambiguous problems and propose improvements in a dynamic organization.
About Meta
Meta builds technologies including Facebook, Messenger, Instagram, WhatsApp, and immersive augmented- and virtual-reality experiences.
Compensation
- Compensation is determined by skills, qualifications, experience, and location; the posting provides no specific pay amount or cadence.
- The posting notes that compensation details may reflect a base hourly rate, monthly rate, or annual salary and do not include possible bonus, equity, or sales incentives.
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