Remote AI Researcher (Mathematics-Oriented)

Role Overview

Can mathematical precision fuel the future of machine intelligence? We believe it can—and we're inviting you to shape that future. As a Mathematics-Oriented AI Researcher working remotely, you'll join a pioneering team that's redefining what's possible in artificial intelligence through elegant, theory-driven breakthroughs. This isn’t about ticking boxes or reproducing models; it’s about uncovering the mathematical truths behind next-generation AI. If you're ready to use logic and innovation to craft a meaningful impact, let’s build something groundbreaking together.

Key Responsibilities

Research That Moves the Field

Your explorations in theoretical math won’t sit in dusty journals. Instead, they’ll shape models used by thousands of engineers and researchers worldwide. You’ll refine neural architectures, develop new optimization algorithms, and question fundamental assumptions underpinning today's systems.

Cross-Functional Collaboration

Partner with applied scientists, ML engineers, and product teams to connect mathematical ideas to real-world systems. Whether it's over a Zoom brainstorming session or an asynchronous discussion on Notion, your voice will influence everything from data pre-processing to how we measure model fairness.

Advanced Problem Solving

You’ll frame and solve open-ended problems where the path isn’t obvious. Think: designing a new regularization technique grounded in algebraic geometry or proving convergence properties for stochastic processes used in distributed learning.

Indicators of Success

Tangible Mathematical Impact

Success means publishing a novel result that unlocks performance gains for large-scale models or helping a product team reduce model inference time by 40% after a strategic shift in architecture. It means influencing roadmaps not with buzzwords but with clarity and proof.

Continual Learning and Growth

We're not here to micromanage. You’ll have the freedom to dig deep, explore ambitious ideas, and choose problems worth solving. If a concept takes two weeks to develop and another to test, that's time well spent—because rigor matters.

External Contributions

We support and encourage submissions to conferences, community talks, and open-source contributions. Whether you're presenting a poster at NeurIPS or publishing a whitepaper on mathematical priors in generative models, you’ll have full backing to share your insights.

Candidate Profile

Mathematical Expertise

You navigate linear algebra, probability theory, statistics, graph theory, or information theory like a second language. You’ve likely used them to decode complex ideas, from tensor decomposition to spectral methods.

Research-Oriented Thinking

You’ve probably spent hours tweaking proofs, but you also know when to pivot and ship an approximate solution. You thrive on clarity and iteration, not perfectionism.

Strong Communicator

You simplify dense concepts—whether it's through a well-crafted Slack post or whiteboard-style Loom walkthrough. Cross-team peers rely on your clarity.

Educational & Professional Background

Maybe you hold a Ph.D. in mathematics, computer science, or theoretical physics. Or perhaps you've published work in venues like ICLR or COLT. Either way, you bring a passion for math-driven AI that translates into results.

Remote Work Environment

Global Team, Unified Culture

Our stack supports async deep work and real-time sync: you’ll collaborate via tools like Notion, GitHub, Zoom, and Overleaf. You can be in Berlin or Bangalore—what matters is your mind, not your location.

Work-Life Balance Across Time Zones

While we’re globally distributed, we aim for meaningful overlap with the GMT-5 to GMT+2 time zone range to facilitate smooth collaboration. You’ll have space for both focused flow and shared discovery.

A Culture Built for Focus

You won't be buried in meetings. We believe in clarity over chaos, quiet over noise, and that breakthroughs come when minds are respected, not rushed.

Tools and Technologies

Programming and Frameworks

You’re proficient in Python, especially for building experiments in NumPy, JAX, or PyTorch. You’ve likely dabbled in Julia, Matlab, or R for high-performance modeling.

Symbolic Computation Tools

Tools like Mathematica, SageMath, or Sympy aren't just optional—they help you model ideas before coding them. Your workflow embraces both abstraction and experimentation.

Development Practices

From git workflows to Docker containers, your work isn’t just elegant—it’s reproducible. You know research matters more when others can build upon it.

Compensation and Benefits

Competitive Salary

This is a fully remote position with an annual compensation of $80,000. It reflects our respect for the level of thinking and ownership you bring.

Comprehensive Benefits

Alongside your salary, you'll receive generous PTO, a yearly learning budget, wellness reimbursement, and flexible scheduling, allowing you to live and work on your terms.

Call to Action

If you're excited to apply mathematical thinking to solve meaningful AI problems—and want your work to ripple across product, research, and policy—we're excited to hear from you. Let’s build something purposeful together.