Help & Supportcareers@gravityer.com
matthewkhoriaty2026@u.northwestern.edu matthewkhoriaty@gmail.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
trading-bot
June 18, 2026 – Present
Educational, math-first algorithmic day-trading lab for US stocks: backtesting, live data, and a beautiful concept-explaining web page.
View Projectcode-detection-confound
May 22, 2026 – Present
code-detection-confound — GitHub repository
View Projectdecoding-decoding
May 8, 2026 – Present
What happens if LLMs predict their own decoding parameters?
View Projectai-safety-math-explainers
May 5, 2026 – Present
ai-safety-math-explainers — GitHub repository
View Projecticl-diversity
March 7, 2026 – Present
ICL diversity metric: measures LLM output diversity via progressive conditional surprise
View Projectclaude-code-settings
February 25, 2026 – Present
claude-code-settings — GitHub repository
View Projectinterpretable-fine-tuning
February 6, 2025 – May 19, 2025
Training components that act on SAE latents so that it is describe what was learned during fine-tuning
View Projectsae_jailbreak_unlearning
January 14, 2025 – November 21, 2025
Investigating how well intervening on Sparse Autoencoder internals prevents adversaries from accessing dangerous knowledge.
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and research-oriented, focusing on advanced AI/ML topics. This indicates a strong drive for independent learning and exploration, which could be a good fit for a research-heavy or innovative team. However, the lack of diverse project types (e.g., production systems, client-facing applications) or team-based work makes it challenging to fully assess cultural fit in a collaborative, product-focused environment. The projects align well with the 'Data Scientist' target role, especially one with an emphasis on AI/ML research and development.
Soft Skills & Operational Fit
The candidate's project descriptions are concise but lack detail regarding problem-solving approaches, collaboration, or impact, making it difficult to assess soft skills or operational fit. The absence of formal work experience or team projects limits insight into collaboration or communication styles.