Remote Machine Learning Mathematician

Shape the Future of Machine Learning from Anywhere

Do you see connections others miss? Imagine contributing mathematical breakthroughs that redefine how models learn, predict, and adapt—right from your home office. As a Remote Machine Learning Mathematician, you'll do more than build algorithms; you'll chart new territory in advanced mathematics and push the boundaries of machine learning. Here, deep theory meets practical impact, and every insight you generate could drive the development of more innovative technology used by millions worldwide. With a bold annual salary of $187,824, this role rewards intellectual ambition, innovation, and collaborative spirit.

Why This Role Matters

Machine learning is only as powerful as the mathematics behind it. Your work will elevate our approach to model interpretability, optimization strategies, and statistical rigor. Imagine a place where your expertise in high-dimensional probability or optimization theory doesn’t just live in a research paper—it shapes real-world products, from medical diagnostics to next-gen search. You’ll join a team where theory is treasured and creative solutions drive product launches that genuinely matter.

Core Contributions & Impact

• Pioneer new approaches to supervised, unsupervised, and reinforcement learning, blending mathematical rigor with hands-on experimentation. Your theorems and proofs won’t sit on a shelf—they’ll power models deployed in production environments with global reach.
• Translate complex mathematical insights into intuitive frameworks and actionable roadmaps for engineers, product leads, and non-technical partners. You’ll be the reason our teams simplify and scale what seems impossible.
• Analyze, design, and refine learning architectures using advanced linear algebra, calculus, probability, and information theory. Every equation you write could improve the lives of thousands.
• Leverage Bayesian inference, statistical learning theory, and stochastic optimization to help products deliver fairer, faster, and more robust results. Your ability to see around corners will inspire bold new features and greater confidence across teams.

What It’s Like to Work Here

You’ll partner with researchers, data scientists, and engineers to bring elegant theory to high-impact applications. Our stack includes cloud-based Jupyter environments, distributed training platforms, and powerful GPU clusters. We believe remote should mean connected—so whether you’re sharing ideas on Slack or co-creating in real-time with Figma and Notion, your voice always matters. Deep focus is valued, but you’ll also find energy in virtual stand-ups and idea jams.

We move quickly, but you’ll always have space to focus intensely, explore hypotheses, and turn breakthroughs into reality. Our culture thrives on curiosity, humility, and a commitment to continuous learning. Whether you’re presenting a new approach to regularization at a virtual brown bag or mentoring a teammate, you shape not just our models but our team ethos.

Tools & Technologies

You’ll have access to a robust suite of tools: Python, R, MATLAB, TensorFlow, PyTorch, Scikit-learn, and Julia are just the beginning. For distributed data, think Spark and Dask. Visualization? Matplotlib and Plotly. We empower you to prototype, experiment, and scale with the best technology stack—because your time is precious, and your ideas deserve the fastest path to impact.

Essential Skills & Experience

• Profound knowledge of machine learning theory, statistical learning, and optimization.
• Advanced understanding of mathematical foundations: fundamental analysis, functional analysis, numerical methods, and stochastic processes.
• Mastery of at least one primary programming language for machine learning (Python preferred), with proven ability to translate mathematical concepts into code.
• Practical experience developing and validating complex models in production environments.
• You simplify complex ideas—whether it’s over Zoom or Slack—building alignment and excitement across both technical and non-technical teams.
• Doctorate or equivalent advanced degree in mathematics, statistics, computer science, or a closely related field.

How You’ll Grow

Every day, you’ll expand your impact—helping shape the standards for ethical AI, interpretability, and reproducibility. Lead seminars on generative models, experiment with novel loss functions or advise on integrating deep learning with classical statistics. Your growth here is defined by your curiosity and willingness to question the status quo. We champion learning and support every spark of insight, knowing that’s where the next leap will come from.

The Mindset That Thrives Here

You question assumptions and back up ideas with proof—then test, refine, and push further. You’re not afraid to challenge consensus, but you value collaboration over competition. When you find a better way, you share it openly. When you see a colleague’s idea take flight, you celebrate it. Here, your mathematical intuition meets a community that cares about building technology responsibly and for good.

Ready to Make Your Mark?

If you’re motivated by solving big, meaningful problems and want your expertise to ripple outward into tools, products, and teams—this is your invitation. Let’s build something remarkable together, starting today.