Intermediate Software Engineer III (ML Infrastructure)

OUR VISION
At EarthDaily Analytics (EDA), we strive to build a more sustainable planet by creating innovative solutions that combine satellite imagery of the Earth, modern software engineering, machine learning, and cloud computing to solve the toughest challenges in agriculture, energy and mining, insurance and risk mitigation, wildfire and forest intelligence, carbon-capture verification and more. 
EDA’s signature Earth Observation mission, the EarthDaily Constellation (EDC), is currently under construction. EDC will be the most powerful global change detection and change monitoring system ever developed, capable of generating unprecedented predictive analytics and insights. It will combine with the EarthPipeline data processing system to provide unprecedented, scientific-grade data of the world every day, positioning EDA to meet the growing needs of diverse industries.
OUR TEAM 
Our global, enterprise-wide team represents a variety of business lines and is made up of business development, sales, marketing and support professionals, data scientists, software engineers, project managers and finance, HR, and IT professionals. Our Data & Platform team is nimble and collaborative, and in preparation for launching a frontier and disruptive product in EDC, we are currently looking for an Intermediate Software Engineer III to join our crew! This is a Vancouver-based hybrid position with 3-days per week in-office required.
PREPARE FOR IMPACT!
As an Intermediate Software Engineer, you will design, build, and optimize the large-scale cloud-based data ingest, training, and benchmarking infrastructure that powers EarthDaily’s agriculture geospatial foundation model development, and contribute to innovations in foundation model development and downstream application of the model. You will be a member of the Engineering team with high impact activities on the future of our organization, creating critical technology to leverage the EarthDaily Constellation’s unique temporal, spectral, and spatial characteristics.
KEY RESPONSIBILITIES:

• Design, implement, and optimize algorithms and infrastructure for large-scale cloud‑based data ingestion and preprocessing pipelines for EO and related datasets.
• Build and optimize algorithms and infrastructure for large‑scale distributed training and benchmarking of geospatial foundation models.
• Develop benchmarking tooling for ML experiment management, metrics, and comparison of EarthDaily geospatial foundation model and open source geospatial foundation models
• Contribute to foundation model architecture and fine tuning for agriculture applications
• Participate in sprint planning, sprint reviews, sprint demos, sprint retrospectives 
• Ensure technical documentation and systems are created, maintained and operational 
• Grow your skillsets and share your experiences with the team 

• Degree in Computer Science, Math, Physics, Engineering, Geography, GIS or equivalent  
• Higher level education in machine learning, data science, remote sensing, or related field is an asset.
• 5+ years of software engineering experience 
• 1+ years of professional experience in developing large scale cloud-based (AWS, Azure, GCP) data and/or ML training infrastructure solutions with a proven track record of delivering complex or algorithmically sophisticated functionality 
• 3+ years of professional experience developing machine learning techniques to solve complex geospatial data science problems
• Experience using and developing API-driven architectures an asset
• Experience working with remote sensing systems and/or data an asset
• Experience with Agile development, SCRUM and CICD processes 
• Equivalent combination of education is accepted

• Excellent algorithmic, analytic, problem solving, debugging, optimization and code reviewing skills 
• Good communicator and collaborative approach 
• Physics and/or math knowledge an asset
• Good object-oriented and test-driven design skills 
• Good skills and knowledge of best practices in at least one programming language (e.g. Python, C++) 
• Good knowledge of the Python scientific stack: Numpy, Scipy, OpenCV, Matplotlib, GDAL, etc an asset
• Good knowledge of Python geospatial machine learning frameworks and libraries (e.g. PyTorch, TorchGeo) an asset
• JupyterLab or JupyterNotebook rapid prototyping skills an asset
• Database technologies and data lifecycle methodologies an asset
• Self-starter and self-learner attitude with the ability to manage and execute with minimal supervision 
• Ability to take initiative, commit and thrive in a fast-paced, deadline-driven environment 

To make the most innovative products that serve our customers, we recognize the role that each of us plays in Diversity and Inclusion at EarthDaily. We draw from our diverse crew of exceptional team members and encourage and empower our team members to express themselves regardless of identity, race, colour, ancestry, place of origin, religion, marital status, family status, physical or mental disability, sex, sexual orientation and gender identity or expression. 

• Competitive compensation and flexible time off 
• Be part of a meaningful mission in one of North America's most innovative space companies developing sustainable solutions for our planet
• Great work environment and team, with a waterfront head office location in Vancouver, BC.