X is Alphabet’s moonshot factory. We are a diverse group of inventors and entrepreneurs who build and launch technologies that aim to improve the lives of millions, even billions, of people. Our goal: 10x impact on the world’s most intractable problems, not just 10% improvement. We approach projects that have the aspiration and riskiness of research with the speed and ambition of a startup.
About the team:
We are an early stage X team focused on using machine learning to build predictive models that could be used in a variety of fields and industries. You will be joining the founding team in a fast-paced, start up environment with a lot of room to grow your role within the team. We are a small team and there is plenty to do for someone interested in building cutting edge technology and building world-class predictive models.
About the role:
You will lead and own the project’s modeling infrastructure track. You will build, scale and optimize a wide range of ML, statistics and causal inference algorithms so they can be employed to analyze very large datasets. You will also support other team members in developing and deploying models of complex phenomena, collaborating with them to improve their use of modeling tools, data and compute infrastructure to make our entire team more productive. You will be a hands-on engineer and bring ML infrastructure expertise to the team. We are looking for passionate and driven people, who are comfortable moving between creative, big-picture thinking and tactical execution in a fast-paced, fluid environment.
How you will make 10x impact:
- Be an active engineer and technical expert of the project. We want you to be a builder and think like an owner!
- Develop and maintain computing and data infrastructure to support our modeling efforts.
- Improve our algorithms and their implementations to maximize their performance and parallelism.
- Collaborate with other team members to leverage the temporal, spatial or other structure of each problem or dataset to enable us to model it efficiently.
- Collaborate with other team members to improve the generality, accuracy or other capabilities of our modeling algorithms.
- Collaborate with other team members to develop ways to multiple models of the same or related phenomena (e.g. real estate + climate, etc.)
What you should have:
- PhD in a STEM field such as CS, Physics, Earth Sciences, or Mathematics/Statistics.
- Research or Industry experience in
- Implementing ML, statistics or causal inference algorithms.
- Infrastructures for ML, cloud computing and parallel computing.
- Training and deployment of ML models at scale.
- Time-series analysis, predictive modeling and/or multi-model coupling.
- Proficiency in Python and experience with TensorFlow. Experience in Deep Learning research and a wide variety of Deep Learning Models.
- Experience iterating on existing ML models and dictating data engineering processes.
- Willingness to work on ambiguous, ill-defined problems, where the final goals are refined as we learn more about the problem.
It’d be great if you also had these:
- Demonstrated personal passion to apply your talents towards solving big global problems.
- Startup / early product development experience.
- A growth mindset: you want to learn as fast as possible, value feedback and are committed to grow fast in the role.
- Excellent at prioritization and time management.
- Solid written and verbal communication skills.
- Openness to working across the stack - data pipelines to ML models to UI.
- An ability to thrive in unstructured work environments with rapidly changing requirements.
At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please contact us at: email@example.com.