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Design a modular, open-source AI architecture focused on low-complexity solutions (e.g., rule-based or lightweight ML models) to aggregate and analyze data from up to 10 IoT types of sensors (weather, soil, water, audio).Integrate external open data source (e.g., satellite, public biodiversity records) using cost-effective APIs or free datasets.
Develop and deploy basic models for:Anomaly detection (e.g., sudden changes in temperature, humidity, or soundscape).Simple biodiversity verification (using audio or image data, leveraging pre-trained models where possible).Implement a lightweight natural language interface for querying sensor data and receiving simple, actionable recommendations.
Design a minimal, intuitive interface for Android tablets or web, focused on clear visualization of environmental trends and alerts.Ensure the interface is accessible to non-technical users and supports basic community input (e.g., manual species observations).
Prioritize energy-efficient, low-footprint AI solutions (e.g., edge computing, efficient cloud use) to minimize environmental and operational costs.Document and track the system’s energy use and environmental impact, aligning with “green AI” best practices.
Collaborate with the project director and local stakeholders to tailor system features to bio-regional needs.Deliver basic training materials and documentation to enable future community-led customization and maintenance.
Milestone 1: Sensor integration and data pipeline (Month 1)Milestone 2: Core AI model deployment and basic interface (Month 2)Milestone 3: Community testing, feedback, and refinement (Month 3)
Demonstrated experience in AI/ML for environmental or sensor-based applications, with a focus on lightweight, sustainable solutions.Strong background in information architecture and interface design for non-technical audiences.Familiarity with IoT integration, open data sources, and open-source AI tools.Commitment to sustainability, energy efficiency, and community empowerment.Ability to deliver results within strict budget and timeline constraints.
AI Engineer Job Description
Project Overview
Project Lovelock is building a global network of AI-powered “Living Libraries” to empower communities and land stewards with real-time, actionable insights about their local environments. Our mission is to make environmental intelligence accessible, playful, and actionable-leveraging IoT sensors, open data, and community knowledge to foster ecological stewardship.
Find more details in our Emerging
Role Purpose
We are seeking a hands-on, visionary AI engineer to design, prototype, and deploy a lightweight, energy- and cost-efficient environmental intelligence system. You will architect and implement core AI features-prioritizing sustainability, modularity, and usability-within a tightly constrained $15,000 budget.
Scope of Work
1. System Architecture & Integration
2. Core AI Functionality
3. User Experience & Interface
4. Sustainability & Efficiency
5. Community Engagement & Customization
6. Milestone Delivery
Budget (Indicative) 2
Category
Estimated Cost (USD)
AI Lead (part-time/contract, 3 months)
$6000
Sensor integration & hardware
$3,000
Cloud/API costs & infrastructure
$1,500
UI/UX design (contract/freelance)
$2,000
Community engagement & documentation
$1,000
Contingency
$1,500
Total
$15,000
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Note: This budget prioritizes a lean, rapid-prototyping approach using open-source tools, pre-trained models, and minimal hardware to maximize impact per dollar.
Required Experience & Skills
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