Lead Research Scientist

Requirements

• Deep Research Expertise: PhD or equivalent deep industrial experience in Computer Science, Math, or Physics.
• Public Track Record: A portfolio of patents, impactful open-source contributions, or first-author publications in top-tier conferences.
• Mastery of the Modern Stack: Expert in PyTorch or JAX.
• Specialization in Structure & Generation: Deep experience in Generative AI, Graph Neural Networks, or Geometric Deep Learning.
• Engineering Rigor: Write clean, modular, production-ready code.
• Communication: Ability to explain complex mathematical concepts to various stakeholders.

Nice-to-Haves

• Graph Learning Expertise: Experience with Graph Neural Networks or Geometric Deep Learning.
• Generative Media: Hands-on experience with Diffusion models or Multimodal LLMs.
• Performance Optimization: Experience in porting models to constrained environments or optimizing inference for real-time interaction.
• Domain Knowledge: Previous work in Computational Creativity, HCI, or building tools for thought.

What You'll Be Doing

• Pioneer Novel Architectures: Design and train custom architectures that fuse multimodal inputs.
• Bridge Theory and Production: Translate academic theory into scalable production systems.
• Define the Technical Strategy: Make critical decisions on model selection and strategies.
• Mentorship & Technical Excellence: Elevate the ML research engineering organization through mentorship.
• Solve the "Unsolved": Tackle ambiguous problems creatively.

Perks and Benefits

• Competitive equity package
• Health insurance for you and your family
• Corporate pension plan
• Lunch, snacks, and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance
• Opportunity to work for a globally diverse team