We are recruiting a talented software and/or data engineer to work across several new and existing projects, starting in the Summer of 2022. The exact role and responsibilities will depend on your strengths and interests, but examples of projects include:
- Open source software development and repository management: Translating recent scientific innovations into bullet-proof code and libraries that can be released to the general public through open source libraries.
- Large-scale data engineering: Processing and automating the ETL, cleaning and analysis of vast amounts of structured and unstructured data
- Back-end ops: Building and maintaining high-performance computing infrastructure to enable efficient processing and analysis of petabytes of heterogeneous data
- Front-end software development (Optional, and only if the candidate is interested): For qualified and interested candidates, there may also be opportunities to develop high-impact interactive interfaces to enable users to engage with cutting-edge applications of machine learning and data science.
- Bachelor’s Degree in Computer Science, Information Science, or a related field; or 2+ years of professional experience with object-oriented programming
- Expertise in Python, as well as at least one other object-oriented programming language, such Java/Scala or C/CC++. By “expertise”, we mean that you would be able to code a moderately complex program (such as a CLI version of Scrabble) in syntactically-correct, idiomatic code, without reference materials
- Mastery of *nix command-line tools and scripting
- Excellent communication skills, meticulous attention to detail, excellent coding standards (including careful code documentation), and ability to work with version control
- Experience with *nix sysadmin, DBA, and/or cloud infrastructure deployment (such as Docker or other containerization systems)
- Experience with “big data” technologies such as Hadoop, Spark, GraphX, GraphLab, Kubernetes, ideally including past work with large structured and unstructured datasets
- Applied experience with machine learning, computer vision, remote sensing.
- Good understanding of inferential and descriptive statistics, and working knowledge of statistical programming languages (e.g., R, Julia, Matlab, Stata) and/or libraries for quantitative analysis (e.g., pandas, scikit-learn, tensorflow)
- A cover letter that clearly describes your relevant skills and experiences. Please specifically highlight how you meet the minimum and desired qualifications listed above.
- A CV or resume
- Links to a repository of code that you have written that demonstrates your programming expertise
- Your academic transcripts
- Contact information for three professional references, ideally one or more from an academic institution
The University of California, Berkeley is an Equal Opportunity/Affirmative Action Employer. Please note CEGA will only hire individuals who are eligible to work in the US, either through an Optional Practical Training (OPT) visa or as a result of being US citizen or permanent resident.