Machine Learning Engineer

Role Overview

The Cake is hiring a Senior Machine Learning Research Engineer (full-time, direct hire, remote U.S.-based). This is a research-first position focused on inventing and validating novel ML methods. Production translation is secondary and selective.

What You’ll Be Doing

• Invent and evaluate novel machine learning methods (architectures, learning paradigms, optimization strategies, representation frameworks)
• Conduct first-principles research on unstructured and multimodal data
• Design rigorous experiments (including failure analysis and ablation studies) to validate ideas
• Translate validated research into production-grade systems when appropriate
• Collaborate to develop defensible IP (e.g., patents and internal research artifacts)
• Author/co-author research papers, technical reports, and internal whitepapers
• Influence long-term R&D direction through original thinking

Must-Haves (Non-Negotiable)

• PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, or closely related field
• 5+ years post-PhD working on research-level or research-driven ML problems
• Demonstrated original ML innovation, such as:
  • Peer-reviewed publications with meaningful citations
  • Patents or patent-pending ML methods
  • Novel architectures, algorithms, or learning frameworks
• Deep experience with modern ML architectures (e.g., Transformers, generative models, representation learning)
• Strong proficiency in Python and at least one systems language (C++ or Java)
• Ability to move from theory → experimentation → defensible implementation
• U.S.-based professional experience strongly preferred

You’ll Stand Out If You…

• Have authored/co-authored highly cited ML research
• Have contributed to patents or protected ML IP
• Have experience in research labs or innovation-driven R&D teams
• Have created new datasets/benchmarks or evaluation methodologies used by others
• Can clearly explain what is novel and why it matters
• Have shown long-term ownership of complex research efforts
• Thrive in ambiguous environments where solutions must be invented