2026 PhD / Masters Residency - Machine… at X, The… · Mountain…

Summary: X, The Moonshot Factory is focused on tackling climate change through innovative technology. The role involves developing neural reasoning capabilities and applying machine learning models to real-world problems in sustainability and finance. Responsibilities: - Explore the potential of leading edge reasoning models to solve large-scale planning and optimization problems in collaboration with human experts - Leverage neural/foundation modeling techniques to build models of and generative optimization algorithms for a wide range of real-world modeling tasks - Translate your expertise in neural modeling to the rest of the team and apply it to solve real-world engineering problems related to climate sustainability and the carbon economy - Collaborate with X project team to experiment and build novel insights to finance, risk management, portfolio management, and derivatives valuation problems - Rapidly develop prototypes of artificial intelligence, machine learning models applied to sustainability and finance problems - Apply the latest in data science techniques to build and deploy data pipelines and exploratory data analysis on large-scale datasets - Develop value chain maps, evaluate costs and revenues to assess and recommend areas in which to de-risk the project - Work cross-functionally with experts across, X, Alphabet, and academia - Engage with the intern community during the program (attending tech talks, colloquium, and learning moonshot thinking), and most importantly HAVE FUN! Required Qualifications: - Masters or PhD student in a STEM field (financial engineering, risk management, operations research, math/statistics or other quantitative field) - Strong knowledge of financial and probabilistic theory, as applied to financial markets - 5 years experience with simulations of real-world phenomena (e.g., physical, biological, ecological, sociological) - Understanding of decarbonization and carbon removal technologies, as well as carbon markets - Fluent in Python, C++, SQL, databases, scripting, Matlab/R, SAS, and data visualization - Strong knowledge of statistical or machine learning modeling techniques, including Large Language Models - Experience in using distributed computing resources, such as GCP, AWS, Azure or HPC clusters - Very strong strategy and analytical skills. Ability to gather and analyze large quantities of information, and turn them into insightful business recommendations - Good at problem stating and problem solving, and turning ambiguous problem spaces into radical solutions. Must be able to break down problems independently - Can do attitude, willing to learn new tools and content to become an effective thought partner with project teams - Excellent communication skills i.e experience writing strategy docs, experience delivering presentations, and a general openness to liaise with senior external partners - Motivated by making the world a better place through technology, and wanting to be part of a team that makes this happen Preferred Qualifications: - Degree in a science, math, or engineering field - An ability to thrive on ambiguity, setting own goals and effectively delivering them in a fast-changing environment - Adept at influencing without authority, working cross-functionally with different teams in order to drive decision making Required Skills: Financial theory, Probabilistic theory, Simulation modeling, Decarbonization technologies, Carbon removal technologies, Carbon markets, Python, C++, SQL, Databases, Scripting, Matlab, R, SAS, Data visualization, Statistical modeling, Machine learning, Large Language Models, Distributed computing, Google Cloud Platform, Amazon Web Services, Microsoft Azure, High Performance Computing clusters, Analytical skills Benefits: Get paid competitively, Receive benefits