Member of the Technical Staff - Product

We're leveraging AI to solve one of the most consequential challenges in the pursuit of technical progress : the distribution of scientific innovations to the real world. We're well-funded with top investors and are building a world class team.

For innovations to have broad impact, they must scale beyond the lab. For too long, the transfer of discoveries from lab bench to real-world application has relied on informal handoffs, tacit know-how, and opaque processes and is littered with failed attempts and learnings buried in lab notebooks. The industry has quietly accepted this agonizingly slow process and inability to broadly reproduce and distribute new discoveries. We're determined to support a new paradigm that ensures new scientific innovations can be more robust, interpretable, and transferable.

We are building processes and cutting-edge AI tools that aim to illuminate and streamline these critical transfers of knowledge. We learn as much, if not much more, from failures as successes, transforming experimental science into robust, scalable solutions.

We aren't building AI to replace human ingenuity, but rather AI that can be a better partner in understanding and translating that ingenuity to new domains. We seek to build tools that help scientists spend less time documenting and debugging and more time doing the exploration they love. To be clear : we believe this will become critical infrastructure. Without solving for scale and knowledge distribution, the discoveries that will be enabled by great scientists at the bench and generative AI designs will fail to reach their end customer : us.

Work with us :

Your impact starts here. We enthusiastically invite applicants across a broad range of expertise and experience to apply. Maybe you have expertise at the bench and have seen reproducibility challenges first hand, maybe you're one of the first people to read a new AI benchmarking paper that comes out, or maybe you have a knack for quickly developing and deploying solutions that make mundane tasks easier. Each candidate that joins the team will be a member of the technical staff, and compensation will depend on experience and responsibility. Our team works across AI and biotech innovation, so even if you apply for one role, we may consider you for others as well.

We think in-person collaboration is invaluable, but recognize that talent is broadly distributed, and are open to flexible working arrangements. We're based in Cambridge, MA, but invite applications from all geographies.

What you can expect from us :

Opportunity to join a creative and mission-oriented founding team and build

with

us, from the ground up

We have a bias for action and are obsessed with solving our customers' real problems

We also love bold and audacious science, enabling moonshots, and are motivated to work with and across the entire ecosystem, enabling new and better futures for ourselves and our families

We also offer a full HR comp stack to include competitive salary, equity, and benefits

What you'll accomplish with us :

Lead qualitative and quantitative research efforts to understand user workflows, pain points, and tacit practices—both in our internal labs and those of our partners.

Translate messy, real-world insights into structured requirements that drive product design, system architecture, and AI model development.

Develop user personas, journey maps, and usability testing frameworks to inform iterative product development cycles.

Bring cross-functional initiatives from concept to delivery. Establish milestones, communication cadences, and decision-making frameworks.

Become customer obsessed. Initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.

Develop intuitive, usable tools and UIs in partnership with the engineering team to support scientist workflows.

Partner with scientists, engineers, and designers to prototype and evaluate interfaces and tools that improve documentation, decision-making, and experimental reproducibility.

Help define and implement product standards for usability, accessibility, and cross-platform cohesion across the experimental ecosystem.

Identify opportunities to reduce friction in data capture, tacit knowledge transfer, and human-AI collaboration.

Support customer deployments by embedding into partner labs, piloting new workflows, troubleshooting edge cases, and capturing lessons learned.

Support onboarding and training with customer-embedded scientists to ensure product adoption and feedback loops are tight and actionable.

Requirements :

Experience in human-computer interaction (HCI), cognitive science, UX research, product design, or a related field.

Demonstrated ability to turn ideas into functional prototypes. Ability to build quickly, test often, and refine thoughtfully—balancing prototypes with production quality as the company scales.

Demonstrated ability to lead user research and synthesize findings into actionable design or product decisions—especially in complex or technical domains.

Experience designing or improving tools for expert users, particularly in scientific, technical, or data-intensive environments.

Comfort working at the intersection of product, engineering, and domain-specific users (e.g., bench scientists, ML researchers).

Excellent communication and storytelling skills—able to advocate for customer needs while navigating technical and strategic constraints.

Additional preferences :

Experience in a scientific or research-intensive environment—academic labs, biotech R&D, national labs, or similar.

Familiarity with experimental workflows, lab automation, or scientific instrumentation.

Experience building AI / ML-powered products from ideation to deployment

Startup or early-stage experience preferred; comfort with ambiguity and rapid iteration is a must.

Ability to clearly communicate technical concepts to cross-functional teams and collaborate on projects spanning AI, biology, and product.

Ideal candidates are located within commuting distance from Cambridge, MA.

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