Environmental Data Scientist (AI/ML)

AIS•La Jolla, CA

3d•Onsite

About The Position

A.I.S., Inc. (AIS) is seeking an Environmental Data Scientist (AI/ML) to support the SWFSCs Ecosystem Science Division (ESD). This role focuses on developing and operationalizing Artificial Intelligence/Machine Learning (AI/ML) workflows for the automated processing and analysis of large-scale imagery datasets. These datasets are collected using advanced technologies such as underwater glider cameras, aerial imaging systems, animal-borne video loggers, and remote trail cameras for monitoring marine and terrestrial environments. The specialist will be responsible for evaluating existing methods, creating integrated data management systems, deploying models in cloud environments, and enhancing the efficiency and scalability of ESD's analytical capabilities.

Requirements

Master's Degree in a related field plus two (2) years' experience.
Demonstrated experience coding in Python, R, and/or C/C++.
Experience developing automated workflows for data processing or analysis.
Experience maintaining application software and data management tools.
Must be able to work in the U.S.

Nice To Haves

Ph.D. may be substituted for master’s degree and 2 years of relevant experience.
Experience developing or applying computer vision and machine learning models for ecological or environmental image analysis.
Familiarity with Google Cloud Platform (GCP) services including virtual machine deployment and cloud storage.
Experience with edge computing platforms or embedded systems for field data collection.
Background in marine, environmental, or fisheries science contexts.

Responsibilities

Develop new capabilities including data management systems and integrated workflows to increase efficiency of processing and preparing data for research projects and AI/ML model development.
Explore various optical imagery datasets for the design, development, evaluation, and application of AI/ML capabilities, edge computing, and automated analytic workflows.
Develop or adapt software for optical imagery processing and web-based dashboards using Python and/or C/C++.
Deploy models using virtual machines (VMs) in the Google Cloud Platform.
Execute technical research projects, track progress, and present technical material in a variety of forums including weekly team meetings, conferences, working groups, and program reviews.
Create standard operating procedures (SOPs) for implementing AI/ML pipelines and instruct additional staff on their use.
Submit monthly progress reports reflecting the status and progress of all tasks.