About Basis
Basis is a nonprofit applied AI research organization with two mutually reinforcing goals.
The first is to understand and build intelligence. This entails establishing the mathematical principles of reasoning, learning, decision-making, understanding, and explaining, and constructing software that embodies these principles.
The second is to advance society’s ability to solve intractable problems. This involves expanding the scale, complexity, and breadth of problems we can solve today and, more importantly, accelerating our ability to solve problems in the future.
To achieve these goals, we are building both a new technological foundation inspired by human reasoning, and a new type of collaborative organization that prioritizes human value.
About the Role
Strategic Systems Engineers at Basis serve as neutral integrators across our research and engineering portfolio, inspired by the legendary Bell Labs model. You will coordinate cross-project technical work, identify shared components and dependencies, develop new program directions, and ensure Basis makes the most effective use of resources as we scale.
We are looking for people who possess both exceptional technical depth and systems thinking breadth. The ideal Strategic Systems Engineer understands whole or large parts of our technical operation—from core algorithmic research through commercial deployment—and can see connections others miss. You will not have direct authority over researchers or engineers, but will influence through technical credibility, problem-finding acumen, and trusted relationships.
This role is distinguished by your ability to keep abreast with fundamental research developments while staying grounded in practical deployment challenges. You channel commercially valuable problems to research teams, map shared technical components across projects, and prevent duplicate work through coordination rather than command.
Basis is a collaborative effort, both internally and with our external partners; we are looking for people who enjoy facilitating work on problems larger than ones any individual can tackle alone.
We expect you to:
- Have demonstrated exceptional technical ability across both research and engineering. This could be evidenced by publications at top-tier venues (NeurIPS, ICML, ICLR, PLDI), significant open-source contributions, or leadership of complex technical programs that spanned research and production.
- Possess deep understanding of AI/ML fundamentals including probabilistic programming, causal inference, neural architectures, and the specific research areas Basis pursues (reasoning, learning, decision-making).
- Have experience coordinating cross-functional technical initiatives without direct authority. You know how to build trust, influence through technical credibility, and drive alignment across autonomous teams.
- Exhibit systems thinking at scale. You can understand complex interdependencies, anticipate downstream impacts of technical decisions, and see both forest and trees simultaneously.
- Maintain awareness of research frontiers while understanding practical constraints. You read papers from top conferences, understand emerging techniques, and can assess which advances matter for Basis mission and commercial applications.
- Be skilled at problem identification and scoping. Following the Bell Labs tradition, you can find the “one or two in a thousand” problems that are both scientifically interesting and commercially valuable.
- Progress with high autonomy under ambiguity. Research coordination inherently involves uncertainty; you thrive in environments where objectives are clear but paths are emergent.
- Be enthusiastic about accelerating societal capability to solve intractable problems through rigorous, high-quality research with clear paths to impact.
Responsibilities
- Coordinate cross-project technical work by maintaining comprehensive understanding of all Basis technical initiatives, identifying dependencies, preventing duplicate efforts, and facilitating knowledge transfer between teams.
- Map shared technical components across projects and work with teams to develop reusable infrastructure that serves multiple efforts.
- Identify high-value research problems by discovering external challenges (from commercial partners, domain experts, or societal needs) and translating them into tractable research questions aligned with Basis capabilities.
- Develop new program directions by synthesizing research capabilities, market opportunities, and societal impact potential into coherent program proposals for leadership consideration.
- Facilitate technical planning by helping teams understand dependencies, resource requirements, and critical path constraints for major initiatives.
- Court and recommend (but not force) researchers to work on high-impact problems. You influence through persuasion, presenting compelling cases for why certain problems deserve attention.
- Optimize resource allocation across technical initiatives by providing leadership with comprehensive view of technical landscape, bottlenecks, and opportunities.
- Maintain awareness of frontier research by attending conferences, reading papers, and staying connected to broader AI/ML research community, then channeling relevant insights to Basis teams.
- Contribute to organizational efficiency by identifying processes, tools, or coordination mechanisms that would improve Basis’s ability to execute at scale without diminishing returns.
- Contribute to the culture and direction of Basis by modeling rigorous technical thinking, collaborative problem-solving, and mission-driven prioritization.
Role Details
Exceptional candidates who may not meet all of the following criteria are still encouraged to apply.
- FT/PT: Full-time
- In-person Policy: We are in the office four days a week. Be prepared to attend multi-day Basis-wide in-person events and maintain regular presence for coordination activities.
- Location: New York City.
- Salary range: Competitive salary.
In addition, the following would be an advantage:
- PhD in Computer Science, Machine Learning, or related field with research and engineering experience.
- Experience at research organizations that successfully transitioned innovations to production (Bell Labs, PARC, Microsoft Research, Google Research, Meta FAIR).
- Track record of identifying research problems that led to significant commercial or societal impact.
- Background in probabilistic programming, causal inference, or program synthesis.
- Experience with technical program management at organizations scaling from 20 to 50+ technical staff.
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