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Software Engineer, Machine Learning, Applied AI

Meta
London, GBR
Onsite
Discovered Today
Applied AILarge language modelsSoftware engineeringAgentic pipelinesReinforcement learning environmentsAI model evaluation

Full Job Posting

Role overview

Join Meta's Applied AI Engineering organization to improve frontier large language models on real-world tasks.

Work with Meta Superintelligence Labs to advance frontier models and AI products.

The organization operates with broad scope, light processes, and fast decisions.

Responsibilities

  • Collaborate across product, design, operations, and infrastructure to build application experiences.
  • Implement custom user interfaces using current programming techniques and technologies.
  • Optimize code quality, efficiency, and performance; provide peer feedback through code reviews.
  • Set team direction, lead major initiatives, mentor peers, and support onboarding.
  • Architect scalable systems; resolve performance and scalability issues and reduce technical debt.
  • Work across programming languages and technologies; own components, features, or systems end to end.
  • Identify model capability gaps and build systems, agentic pipelines, reinforcement-learning environments, and evaluations that produce training signals.

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; understanding of information retrieval, data structures, algorithms, graph theory, or optimization.
  • Knowledge of NLP techniques including text preprocessing, tokenization, and sentiment analysis.
  • Experience integrating AI tools into workflows, implementing responsible AI practices, and developing skills such as prompt/context engineering or agent orchestration.
  • Ability to address ambiguity and improve processes and technology in a fast-moving organization.
  • Experience building synthetic training-data or evaluation pipelines, or verifiable AI training-data environments with quality controls.

About Meta

Meta builds technologies and products that help people connect, find communities, and grow businesses.

Compensation

  • Compensation depends on skills, qualifications, experience, and location; the posting does not state a specific pay amount or cadence.
  • Base compensation may be accompanied by benefits and, where applicable, bonus, equity, or sales incentives.

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