• Develop and implement software applications using a variety of languages, frameworks, and methodologies (e.g. C#, Java, JavaScript, jQuery, HTML, CSS, Spring Framework, Caffeine, Quartz, FHIR, SQL) • Assist clients during user acceptance testing and provide ongoing technical support. • Support data security review procedures; identify and address concerns for compliance with privacy and security policies when developing and supporting software systems. • Perform data extracts against databases and other data sources, to analyze extracted data and to summarize results. • Other tasks as assigned, including but not limited to crafting academic publications, and other software development and systems integration projects.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As part of our ongoing growth and expansion, we are seeking a dynamic and experienced Scientific Programmer to join our growing team. - Assist with applying hydrographic business logic in Python and SQL to develop and maintain automated bathymetry workflows. These stages may include: - Automated scraping of metadata and data, registration of these data in Postgres, the formulation of JavaScript Object Notation (JSON) metadata, and moving the data to the NBS file system. - Automated processes of data sources, including finding and reading JSON metadata and bathymetry data in GeoTIFF, Geoparquet, Geopackage, and Bathymetric Attributed Grid (BAG) formats in the NBS file system, transforming coordinate reference systems, interpolating data, and writing processed data back to the NBS file system. - Data type conversion between various open and closed geographic information system formats. - Automate coordinate system transformations using NOAA marine geodesy systems. - Maintenance of linear interpolation engines for the automated definition of survey coverage, including the uncertainty associated with the interpolation of estimated depths. - Bathymetry compilation module maintenance and updates. - Data extraction, archival, and delivery engines using PostgreSQL, on-prem and cloud capacity. - Assist with the containerization of new and existing workflows. - Assist with integrating new formats of bathymetry into the NBS, such as BAG 2.0. - Assist with standardizing, optimizing, and improving documentation and code to support the NBS program. - Assist with transitioning the NBS workflow to containers and continuous integration and continuous delivery models. Qualifications - Must have a Bachelor’s degree in GIS, Remote Sensing, Marine Science, Engineering, Biology, Oceanography, or related field. - 5+ years of related experience. - Software development experience, including Python, integrated development environments, debugging principles, continuous integration testing, and automated documentation. - Version control best practices and experience with version control software such as Git. - Container-based software development and deployment platforms experience, such as Docker. - Must be proficient in Geospatial data systems configuration; production techniques; and database manipulation. - Experience with digital cartography, image processing, concept formulation, metadata documentation, software architecture and engineering. - Experience with integration of general software applications, GIS software, statistics, and GIS operation. - Knowledge of different types of remote sensing data and working with the government sector is beneficial. Benefits - Comprehensive healthcare for the employee at no monthly cost. - Healthcare benefit covers medical, prescription drug, dental, and vision. - Personal Time Off (PTO) Policy plus paid holidays. - Highly competitive compensation plan regularly calibrated against industry and location benchmarks. - 401(k) retirement plan with company-matching. - Employee Stock Ownership Plan (ESOP) – we're all company owners! - Flexible spending accounts. - Employee assistance program (EAP). - Short- and long-term disability insurance. - Life and accident insurance. - Tuition assistance/Training/Workforce improvement reimbursement per year. - Spot bonuses for exceptional performance. - Annual Employee Recognition Awards with bonuses. - Employee Referral Program. - Free centralized, self-directed Learning Management System to learn at your own pace. - Personalized career growth plans for every employee.

• Serve as Prolific's technical research partner on customer engagements with AI labs and enterprise AI teams • Advise and prototype bespoke solutions like evaluation methodology, rubric design, and data collection approaches • Own methodology for projects - from scoping through delivery • Build trusted relationships with customer research and engineering teams • Surface patterns from customer work that should become platform capabilities • Work with Services and Account teams to qualify opportunities • Share learnings across the Research Engineering function • Collaborate with product teams to translate research insights into practical applications • Mentor team members on advanced AI concepts

• Architect and implement high-throughput, deterministic data sampling systems capable of feeding distributed training clusters at frontier-model scale. • Design and execute dynamic curriculum learning strategies, creating systems that automatically adjust data distributions (text vs. multimodal) during training to improve model stability and reasoning capabilities. • Engineer the logic for serializing Reddit’s complex conversational trees (threads, subreddits, cross-posts) into optimal training contexts, developing topological data processing strategies that preserve semantic relationships for model understanding. • Formulate and validate statistical hypotheses regarding data mixtures, leveraging advanced sampling theory to minimize bias and maximize token quality. • Design the "Safety-First" ingestion layer: Build automated pipelines for PII redaction, toxicity signals, and quality deduplication upstream of training, working closely with our Safety and Moderation Engineering counterparts. • Bridge the gap between research and engineering by translating theoretical sampling insights into robust, low-latency production infrastructure. • Mentor senior engineers and researchers on system design, numerical correctness, and performance optimization within distributed Python/Rust environments.