Research Engineer, Platform

About the role

You will architect and implement core algorithmic modules that form the mathematical and software foundation of Basis research platforms. You own the translation of novel research ideas into robust, reusable components that empower other teams to build upon them efficiently. This role requires you to balance deep theoretical insight with pragmatic engineering to ensure research advances are not just scientifically sound but also deployable and maintainable. You will identify high-leverage research problems and shepherd them from raw concepts through to concrete, tested implementations. You will collaborate closely with researchers and product thinkers to ensure your work has both scientific integrity and real-world applicability. Your contributions will define the building blocks that accelerate future research and platform capabilities across the organization. You will be responsible for ensuring that the software you produce is as rigorous and insightful as the research it implements.

Key facts

What you'll do

Architect and develop Basis core technology modules such as ChiRho, Effectful, and Weighted to provide foundational algorithmic capabilities for the platform.

Design and implement research-driven features that directly support commercial platform offerings, ensuring they meet high standards of performance and reliability.

Translate complex theoretical concepts into concrete software systems while maintaining clarity, modularity, and extensibility for future work.

Establish clear pathways for research advances to generate impact, whether through commercial deployment, open-source release, or platform integration.

Conduct rigorous experimentation and validation to confirm that new modules behave as intended under diverse and realistic conditions.

Collaborate with research scientists to refine specifications, iterate on designs, and align implementation details with theoretical objectives.

Write comprehensive documentation and high-quality tests that enable other engineers to adopt and extend your modules with confidence.

Champion software engineering best practices that make research code maintainable, debuggable, and scalable across teams and use cases.

Identify and address technical risks early, ensuring that platform components remain robust as requirements and underlying models evolve.

Act as a bridge between cutting-edge research and production systems, ensuring that delivered solutions are both innovative and operationally viable.

Proactively propose improvements to development workflows, tooling, and infrastructure that enhance the efficiency and quality of research engineering.

Evaluate emerging techniques and determine how they can be integrated into existing platform components to sustain Basis's technical leadership.

Contribute to open-source and internal projects in a way that maximizes reuse, reduces duplication, and strengthens the broader research ecosystem.

Partner with cross-functional stakeholders to align technical deliverables with strategic goals and real-world problem domains.

Requirements

You have a strong record of high-quality research, demonstrated through publications at top-tier conferences such as NeurIPS, ICML, ICLR, POPL, PLDI, or OOPSLA.

You have a proven ability to drive software projects from start to finish, evidenced by production-quality libraries, major open-source contributions, or systems that span research prototypes and deployable implementations.

You possess deep knowledge of relevant technical areas including probabilistic programming, causal inference, program synthesis, neural architectures, or other fields central to Basis research directions.

You are proficient in research engineering tools including Python, PyTorch/JAX, version control, testing frameworks, documentation systems, and software engineering practices that ensure maintainable and extensible code.

You understand concrete paths from research to impact, and you think intentionally about how advances can translate into commercial applications, platform capabilities, or community-facing open-source contributions.

You value software quality and reusability, designing modules that are coherent, well-documented, and easy for others to extend as they evolve.

You progress with autonomy and intellectual curiosity, identifying valuable research directions, designing experiments, implementing solutions, and evaluating outcomes with minimal supervision.

You are excited by solving real-world problems and leveraging research to advance understanding of intelligence and tackle intractable societal challenges.

You thrive in a collaborative environment and prefer working on problems that are larger than what you could solve independently.

Nice to have

PhD in Computer Science, Machine Learning, Statistics, or a related discipline with publications at top-tier venues.

Experience at research organizations with a strong track record of productionizing innovations, such as Bell Labs, PARC, Microsoft Research, Google Research, Meta FAIR, or DeepMind.

Contributions to widely used research libraries or frameworks that have achieved broad adoption in the community.

A background that spans multiple complementary areas, such as machine learning and programming languages, causal inference and probabilistic programming, or theory and systems.

Practical notes

This role is full-time.

You will work from our New York Office.

Candidates must be eligible to work in the United States without sponsorship for this position.