This fixed-term (up to 2-year) position will provide research software engineering for the EDF/MethaneSAT project at Stanford. Funded by Professor Rob Jackson, and in collaboration with Stanford's Andrew Ng, this software development position will serve as a lead developer of the machine learning models to detect and characterize global sources of methane emissions in remote sensing data.
Lead the design, development, and deployment of state-of-the-art machine learning-based computer vision models on remote sensing data, including implementing the data processing, modeling, and deployment pipelines with modern toolkits
Collaborate directly with the PI (Principal Investigator) and research team members to gather and assess functional and technical requirements
Champion best practices including requirement analysis, design, implementation, testing, deployment, documentation, and maintenance
-*Other duties may be assigned.
Education and Experience:
Bachelor's degree in computer science, electrical engineering, or related field, and three years of relevant experience, or a combination of education and relevant experience.
Knowledge, Skills and Abilities:
Strong software engineering skills, specifically proficiency with Python. Experience developing deep learning models for computer vision with PyTorch, Tensorflow, or similar frameworks. Working knowledge of modern software development tools including bug tracking and source code version control (GitHub).Demonstrated interest and experience in computational research, software development, and open source tooling and methodologies. Experience working with geospatial and/or remote sensing data is highly desirable as is experience using GIS mapping software and tools.
This position requires that you be able to juggle multiple competing priorities and demonstrate initiative in conceptualizing and moving technical projects successfully to completion. The position must be able to do independent analysis, troubleshooting and problem resolution, but also must work collaboratively with other team members and across organizational group boundaries.
Certificates and Licenses:
Constantly performs desk-based computer tasks. Frequently sit, grasp lightly/fine manipulation. Occasionally stand/walk, writing by hand. Rarely uses a desk telephone, lift/carry/push/pull objects that weigh up to 10 pounds.
May work extended hours, evenings and weekends.
Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu/.
*The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
*Consistent with its obligations under law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
*Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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