Intermediate Software Engineer III; ML Infrastructure

Position: Intermediate Software Engineer III (ML Infrastructure)
Overview  OUR VISION At Earth Daily 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 Earth Daily 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 Earth Pipeline 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 Earth Daily’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 Earth Daily 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 Earth Daily 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
YOUR PAST MISSIONS
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 is an asset
Experience working with remote sensing systems and/or data is an asset

Experience with Agile development, SCRUM and CI/CD processes
Equivalent combination of education is accepted
YOUR TOOLKIT
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…