AI Research Scientist

Key Responsibilities

• Conduct original research in machine learning, deep learning, or related AI fields
• Design and run experiments to test hypotheses and validate new approaches
• Develop prototype models and algorithms that demonstrate novel capabilities
• Publish research findings at top-tier conferences and journals (NeurIPS, ICML, ICLR, ACL)
• Collaborate with engineering teams to transition research prototypes into production systems
• Stay current with state-of-the-art research and identify opportunities for application
• Mentor junior researchers and contribute to the research culture within the organization

Required Skills & Experience

• PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field
• Track record of publications at top ML/AI conferences or journals
• Deep expertise in one or more areas: NLP, computer vision, reinforcement learning, generative models, or optimization
• Strong proficiency with Python and deep learning frameworks (PyTorch preferred)
• Experience designing and running rigorous experiments with statistical analysis
• Ability to implement research papers and reproduce state-of-the-art results
• Strong written and verbal communication skills for presenting complex ideas

Nice-to-Have

• Postdoctoral research experience
• Experience transitioning research into production systems at scale
• Familiarity with large-scale distributed training infrastructure
• Open-source contributions to ML frameworks or research codebases
• Experience mentoring graduate students or junior researchers

Tech Stack

What We Offer

• Competitive salary and equity package
• Flexible remote or hybrid work arrangement
• Health, dental, and vision insurance
• Annual learning and development budget
• Generous PTO policy

Interview Process

1. 1Recruiter phone screen (30 min)
2. 2Research deep-dive: present and discuss a recent paper or project (60 min)
3. 3Technical interview: ML theory and coding (60 min)
4. 4System design: scaling research to production (45 min)
5. 5Research vision and culture fit with team leadership (45 min)
6. 6Presentation to broader team on a research topic (30 min)