Research Software Engineer

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer.

As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Join a dedicated team of nearly 11,000 who are shaping the future we envision. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and is continually named one of the Tampa Bay Times’ Top Workplaces.

 

Summary

The Machine Learning Engineer provides an array of services to support the Department of Machine Learning and its Principal Investigators’ research portfolio. High level responsibilities include but are not limited to: - Administering computing infrastructure and manages databases - Developing professional level software tools for machine/ deep learning applications for cancer research - Participating in the planning, implementation and conduct of software tool in collaboration with team members. - Interacting closely with Investigators and their collaborators in consortium settings. - Training new staff and serves as a resource to other projects involving software development within the department. - Maintaining computer skills, and acquires new ones as necessary. - Maintaining independence: a limited degree of supervision is required for the analysis of data and documentation of results. - Maintaining QA program of software tools, which includes: maintaining familiarity with cutting edge machine learning software and informatics tools.

 

We are looking for a motivated individual to develop open-source software for biomedical data science that will be used at the Moffitt Cancer Center and around the world. Key projects that this individual will contribute to include Galaxy (https://galaxyproject.org/), the NHGRI AnVIL (https://anvilproject.org/) data commons, and efforts to integrate internal Moffitt informatics platforms. An ideal fit for this position is an individual who is excited about developing great software for biomedicine, enjoys learning new technical skills, and excels in a collaborative environment.   This position is part of the Goecks Laboratory (https://goeckslab.org/), which is in the Departments of Machine Learning and Biostatistics and Bioinformatics at the Moffitt Cancer Center. The Goecks Laboratory develops data science methods and software tools to advance cancer research and patient care. Our areas of technical focus are computational infrastructure, cloud computing, and machine learning. Our areas of cancer research include precision oncology and spatial tumor analyses.   Position Highlights: • Contribute to software that will be used at Moffitt and across the world to help advance biomedical research. • Opportunity to developing technical leadership skills by architecting and executing software development projects. • Learn new technical skills in important topics such as machine learning, cloud computing, distributed computing, and data engineering. • Work in a dynamic environment and collaborate with software engineers, data scientists, cancer biology researchers, and physicians.   The Ideal Candidate: • Expertise in the following areas: (1) software development; (2) analysis pipeline development; and (3) machine learning analyses. Expertise using software development and analysis skills in a scientific discipline is preferred. • Experience using open-source software libraries for traditional machine learning and deep learning. Experience using commercial machine learning libraries, experiment tracking software, visualization and reporting software, and scaling libraries is preferred. • Strong knowledge of the Python programming language plus experience in other programming languages such as R, Perl, C#, and Java. Knowledge of data structures, runtime analyses, and continuous integration preferred. • Experience developing web-based and/or scientific software that includes several components and/or libraries, including a database. Experience developing open-source software is preferred. • Enjoys working in a multidisciplinary and collaborative environment.   Responsibilities: • Develop informatics software and analysis tools for machine learning analyses of genomic, clinical, and imaging datasets. (30%) • Provide documentation and user support enabling computational researchers to access and use informatics software. (25%) • Maintain well-curated, highly structured, transparent omics, imaging, or clinical data resources and databases suitable for machine learning. (20%) • Develop software tools to integrate bioinformatics and machine learning software applications with data resources. (20%) • Establish and maintain standards for structured software engineering, including requirements, design, code, test