Software Engineer, Libraries

About the Role

Key Responsibilities

• Collaborate with product managers, machine learning engineers, and library users to translate functional requirements into robust technical specifications and production-ready code.
• Architect, build, and maintain the foundational software of our internal Machine Learning libraries, with a relentless focus on performance, and scalability.
• 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.

Requirements

• 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.
• A commitment to owning the software development lifecycle, including testing, containerization, and CI/CD.
• Expert-level proficiency in modern Python, with a deep understanding of its performance characteristics, design patterns, and packaging.
• Familiarity with building performant and reliable Python systems, including low-level C/C++ extensions (e.g., using pybind11, Cython) and instrumentation for production telemetry (e.g., Prometheus, OpenTelemetry).
• A proactive ownership mindset and the ability to navigate ambiguity.
• Excellent collaboration and communication skills for working effectively with teams and stakeholders.

Nice to Have

• Professional experience GPGPU programming (e.g., CUDA, Triton) for performance optimization.
• Experience building and maintaining widely-used internal or open-source libraries.
• Familiarity with the machine learning development lifecycle and core concepts (e.g., bias-variance tradeoff, common optimizers).
• Familiarity with 3D geometric data structures and algorithms.

Qualifications

• Experience with modern Python programming.
• Knowledge of performance optimization techniques in Python and low-level extensions.
• Experience with containerization, CI/CD pipelines, and system architecture.

Benefits & Perks

• Equity options - share in our success and growth.
• 10% employer pension contribution - invest in your future.
• Free office lunches - great food to fuel your workdays.
• Flexible working - balance your work and life in a way that works for you.
• Hybrid setup - enjoy our new Shoreditch office while keeping remote flexibility.
• Enhanced parental leave - support for life's biggest milestones.
• Private healthcare - comprehensive coverage.
• 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.