Head of Science
At integrate.ai, we are empowering organizations working on the world’s most important problems - from cancer research, to new drug discovery, to more equitable financial products - to solve them without compromising the world’s most sensitive data. Our integrate.ai platform enables privacy-safe AI and analytics collaboration within and between organizations without needing to directly share or move data using cutting edge machine learning and privacy enhancing technologies.
We are hiring a Head of Science to lead our machine learning science team across a range of research and applied science initiatives. If you are a science leader with a track record of leading teams and productizing new machine learning technologies, this is a unique opportunity to drive outsized impact in an ambitious, high performing startup.
Our current emphasis is on federated learning (covering a broad range of ML model types), automated data relevancy evaluation, and privacy enhancing technologies, but we welcome exploration into other domains that support the mission of the company to safely activate the world’s most sensitive data to solve the world’s most important problems.
This is an opportunity to lead a team of exceptional scientists breaking new ground in the development of foundational, privacy-preserving machine learning techniques. Our platform is used across several industries and we work with some of the most innovative organizations to bring their otherwise unused data to light in a way that’s privacy-safe.
The Science Team is one of the three main pillars of the technology organization within integrate.ai, along with the Engineering Team and Product & Design Team. The Head of Science reports to the CTO.
- Responsible for developing and executing the research and applied science agenda across the range of foundational domains relevant to the integrate.ai product roadmap and company mission, including federated learning, automated data relevancy evaluation, and privacy enhancing technologies (such as differential privacy). The agenda must support the short, medium and long term product roadmap and company strategy, representing a set of research and development bets for delivering product value using existing and novel techniques.
- Set the agenda for broader research exploration that balances business urgency with scientific curiosity. This means prioritizing research that supports identified product roadmap needs while still recognizing the need to invest effort into curiosity-driven research that aligns with the long term mission.
- Serve as an active partner in the development of the product roadmap based on current and future research initiatives that demonstrate the art of the possible
- Develop and implement rigorous R&D methodologies across the team, including survey/capture of the state of the art in the literature, internal peer review and collaboration, and internal reporting
- Directly collaborate with Science Team members on their work, providing guidance and direct contributions informed by your research experience and your connection with the existing body of research
- Lead the effort to produce engineering-ready reference implementations of the developed methodologies
- Understand and make effective tradeoff decisions inherent in the implementation and productization of machine learning techniques
- Attract and retain star talent
- Support, develop and manage people
- Engage and energize the team
- Communicate ideas and priorities clearly and in a manner that compels action and results
- Foster a positive, action-oriented culture
- Effectively represent the Science Team and their work to the broader company and leadership
- Responsible for tracking the latest direction of the broader research community while developing and asserting a relevant position for integrate.ai within that community
- Represent integrate.ai in relevant venues and forums where we should be seen as an industry and research leader
- Develop a publication strategy that builds integrate.ai’s credibility with the relevant audiences
- Serve as a bridge to academic and research institutions and drive collaboration where appropriate
- Drive meaningful action with effective and fast decision-making that takes into account the interests of all stakeholders – employees, customers, shareholders, and partners
- Ability to work well through ambiguity, confidence in making tough calls and leading through adversity
- Solution-building skills; proven ability to understand business challenges, structure sophisticated problems, and develop solutions
- PhD or equivalent experience in machine learning or related fields, such as computer science, electrical and computer engineering, or computational statistics
- Experience in a commercial research environment with a focus on implementation and productization
- Track record of recognized research contributions in Machine Learning
- Experience building and leading diverse, high-performing applied research teams
- Experience developing foundational machine learning techniques
- A strong foundation in software implementation of machine learning techniques