Software Engineer, Early Stage Project, X

About X, The Moonshot Factory

X is 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

Our team – Bellwether – operates at the intersection of machine learning, geospatial data, and pressing issues with enterprise customers, governments, and more. We focus on severe weather manifestations of climate change, such as wildfires, and aim to use a wide range of data and analytics to better understand and predict what these events could mean for communities and businesses across the globe. We do this through the detection and classification of the features and patterns of the natural and built worlds, the application of cutting-edge machine learning, and the redesign of the full geo-ML workflow. This work extends into development and production-level work as well, as Bellwether also has a number of products that are live with customers. The result: tools and models that allow a range of industries to better leverage earth observation insights.

About The Role

You will be a hands-on engineer, contributing to all aspects of the project’s development and deployment of applications. We are looking for a motivated generalist with broad experience across systems architecture and design in one or more cloud platforms. Our team is small but mighty and highly collaborative, and values pair programming and cooperative ideation. We are committed to the agile principles and rely heavily on this framework for efficient sprints and cycles. We are looking for passionate and driven people, who are comfortable moving between creative, big-picture thinking. From model design and experimentation to production-level deployment. We operate in a fast-paced, fluid environment as our team moves from early stage development into production phases.

How You Will Make 10x Impact

• Embracing your ability to be a ‘power generalist’, enjoying the fluidity of moving from machine learning to production-level execution. From high level strategy to specific tactics.
• Help execute key decisions on software architecture and features balancing business needs and our technology roadmap, balancing longevity with rapid prototyping
• Contribute as a key team member to the creation of new systems and processes to ensure high quality development, deployment, and maintenance of live applications in production environments
• Create and maintain Google Cloud Platform-based infrastructure for software development and high-volume production systems.
• Present findings to team members, internal and external stakeholders, and help set a direction for future development.
  
  

What You Should Have

• Bachelors of Science in Computer Science or equivalent practical experience
• 3-5 years experience with parts of the machine learning development pipeline: research, experimentation, and ML-ops
• Experience with a wide variety of backend tasks, including code development, designing for and implementing security measures and controls, troubleshooting and debugging, designing and implementing code testing processes, and/or monitoring deployed application’s performance and health.
• Experience with one or more common software design patterns (for example, Observer, Decorator, Visitor, Producer/Consumer, etc).
• Experience working on an early stage project and environment that moves into a production phase
• Experience with open source tools such as: Git, TensorFlow, Apache Beam/Dataflow, Google Compute Engine.
• Experience with one or more general purpose programming languages, including but not limited to Python
• An ability to thrive in an Agile-driven team: iteratively sprinting toward goals and products, contributing new ideas, standards, and processes.
  
  

It’d Be Great If You Also Had These

• Experience working with a wide variety of geospatial data
• Experience interfacing with customers
• Experience in Machine Learning Operations - scaling existing machine learning applications into production
  
  

The US base salary range for this full-time position is $126,000 - $192,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.