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Responsibilities
🔵 Requirements:
◽ Expertise in the Linux operating system.
◽ Proficiency in developing and testing complex solutions in Python.
◽ Experience in cloud-based development, specifically in AWS.
◽ Skill in working with databases, handling big data sets, and building data pipelines.
◽ Experience in writing and maintaining production-level code with knowledge of good practices, including agile working.
◽ Experience in CI/CD toolchains (including git) and containerization (Docker).
◽ (Desirable) Familiarity with 3D data processing (e.g., mesh and point cloud).
◽ (Desirable) Knowledge in the geospatial domain and experience with geospatial data formats.
◽ (Desirable) Experience with Kubernetes and distributed computing.
◽ (Desirable) Skills in developing secure software.
🔵 Responsibilities:
◽ Data Pipeline Development:
→ Streamline and automate the flow of large geospatial datasets.
→ Design and develop tools to maximize the use of company data assets, including AI capability development.
◽ Data Management:
→ Curate and administer Vaarst's data holdings.
◽ Team Collaboration:
→ Work as part of a team focused on MLOps, geospatial data processing pipelines, and related systems.
◽ Large Dataset Handling:
→ Manage and implement pipelines and systems for large datasets, including imagery, video, bathymetry, and 3D models.
🔵 Conditions and Benefits:
◽ Flexible, hybrid working and a 35-hour work week.
◽ 25 days annual leave, increasing to 35 days after 6 years + bank holidays.
◽ Sabbaticals at 4 and 6 years; £500 holiday voucher at 2 years.
◽ Private medical insurance, including dental & optical.
◽ Career and learning development through paid courses, conferences, and events.
◽ Curiosity fund – up to £500 for non-role-related learning.
◽ Up to 10% company bonus.
◽ Pension up to 6% company contribution.
◽ Volunteering day for community contribution.
◽ Enhanced maternity and adoption leave.
◽ Cycle to work scheme.
◽ Recognition & rewards for outstanding work and embodying company values.
◽ Various flexible working options.
◽ Sociable team with monthly socials.
◽ Office located 10 minutes from train station, with balcony, fresh fruit, snacks, and drinks.
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