Machine Learning Software Engineer, Libraries

• Collaborate with product managers and library users to translate functional requirements into robust technical specifications and production-ready code.
• Work closely with our research scientists to productionize novel models and algorithms, integrating them into our core libraries.
• Contribute high-quality, tested, documented, and maintainable code across the library stack, ensuring our core systems are reliable and easy for other engineers to build upon.
• Champion software engineering excellence across the team and company, driving best practices in testing (unit, integration, performance), CI/CD, and system architecture.
• Own your work end-to-end, from ideation and experimentation through to deployment and maintenance in a small, agile team environment.
• Continuously explore and evaluate new techniques and frameworks, helping to guide the technical evolution of our platform.
• Share your knowledge with the team, contribute to our engineering guild, and stay connected with the broader community.

• Professional experience with C++ and/or GPGPU programming (e.g., CUDA, Triton) for performance optimization.
• Experience building and maintaining widely-used internal or open-source libraries.
• Experience applying machine learning to scientific domains, particularly with 3D geometric or simulation data.
• Familiarity with model packaging and serialization techniques (e.g., ONNX, TorchScript).

• A passion for the craft of software engineering and building robust, maintainable systems in a collaborative, cross-functional team.
• Solid software engineering skills, with a focus on writing clean, testable, and maintainable code.
• Strong problem-solving skills, with the ability to diagnose complex issues in a high-uncertainty R&D environment.
• A commitment to owning the software development lifecycle, including testing, containerization, and CI/CD.
• A deep understanding of machine learning fundamentals (e.g., model architectures, optimizers, statistical principles) and the data science lifecycle.
• Strong proficiency in Python's scientific computing and Machine Learning ecosystem (e.g., PyTorch, NumPy, SciPy, Pandas).
• An understanding of how high-level Machine Learning frameworks interact with low-level hardware (e.g., C++/CUDA on GPUs).
• A proactive ownership mindset and the ability to navigate ambiguity.
• Excellent collaboration and communication skills, with an ability to discuss complex technical concepts with both researchers and product teams.

• Equity options – share in our success and growth.
• 5% 401(k) match – invest in your future.
• Flexible working – balance your work and life in a way that works for you.
• Hybrid setup – enjoy our Manhattan office while keeping remote flexibility.
• Enhanced parental leave – support for life’s biggest milestones.
• Private healthcare – comprehensive coverage for you and your family.
• Personal development – access learning and training to help you grow.
• Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.

Salary range:

$120,000 - 240,000 depending on experience 
Seniority will be assessed throughout our interview process