Software Engineer, Machine Learning

Meta Meta · Big Tech · London, United Kingdom

Software Engineer, Machine Learning at Meta in London, UK. The role involves building cutting-edge products, improving existing ones, and advancing user experience. Responsibilities include collaborating with cross-functional teams, implementing UIs, analyzing code, architecting scalable systems, and resolving performance issues. Qualifications include experience with data analysis, programming, information retrieval, NLP, AI tools integration, ethical AI practices, and AI skill development like prompt engineering and agent orchestration.

What you'd actually do

  1. Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
  2. Implement custom user interfaces using latest programming techniques and technologies
  3. Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
  4. Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
  5. Architect efficient and scalable systems that drive complex applications

Skills

Required

  • Programming experience in a relevant language
  • Understanding of information retrieval concepts, such as indexing, querying, and ranking
  • Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Nice to have

  • Masters degree or PhD in Computer Science or a related technical field
  • Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques
  • Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn

What the JD emphasized

  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Other signals

  • integrating AI tools
  • responsible, ethical AI practices
  • ongoing AI skill development
  • prompt/context engineering
  • agent orchestration