Consultant - Machine Learning Engineer - LLM Chatbots
The International Water Management Institute (IWMI), a CGIAR Research Center, is seeking an innovative and multi-skilled candidate to join its office in Colombo, Sri Lanka, as a Consultant - Machine Learning Engineer LLM Chatbots.
The Limpopo River Basin (LRB) is a region of immense environmental and socio-economic significance, extending across Botswana, South Africa, Zimbabwe, and Mozambique. It encompasses a diverse range of ecosystems, including forests, wetlands, and savannahs, supporting a rich variety of flora and fauna. The river and its tributaries provide essential water resources for agriculture, livestock, and fisheries, supporting millions of livelihoods. Despite these invaluable resources, the LRB faces challenges such as hydro-climatic extremes, land degradation, poor water quality, urbanization, and population growth, which threaten biodiversity and weaken local communities' resilience to climate change. The basin also faces increasing competition for access to limited water resources and arable land, with women and youth disproportionately affected.
To address these pressing challenges, IWMI’s new project aims to create a comprehensive Digital Twin of the Limpopo River Basin. The LRB Digital Twin will serve as a virtual representation of the basin's socio-ecological system, bridging the physical and digital worlds. This advanced approach combines environmental data, modeling, and analysis tools with digital technology to enable sustainable and inclusive water management.
The primary objective of this role is to contribute to the creation of a comprehensive Digital Twin of the Limpopo River Basin (LRB) by utilizing the Soil and Water Assessment Tool (SWAT) model to forecast water availability and support sustainable water management practices. The consultant will work on utilizing Artificial Intelligence and machine learning tools to explore how data can extract valuable insights using natural language questions. The idea of the project is to use large language models to query the digital twin database and also to explore computer vision methods to extract insights from images.
DUTIES & RESPONSIBILITIES:
1. Architecture Research Overview:
- Integration setup between large language models and open-source databases in a cloud environment.
- Technologies used and rationale behind their selection.
- Challenges encountered during integration and strategies to overcome them.
- Advantages and potential impact of this integration.
2. Benchmarking Out-of-the-Box Technologies:
- Apply large language models to time series climate data and query natural language questions to extract insights.
- Evaluation criteria for benchmarking: performance, accuracy, scalability, ease of integration, etc.
- Benchmarking results of BART, ChatGPT-4, and other open-source large language models.
- Comparison of out-of-the-box technologies' strengths and limitations in handling queries and data processing.
3. Computer Vision Methods for LiDAR Data Analysis via Natural Language Queries:
- Introduction to computer vision techniques applied to LiDAR data analysis.
- Exploration of natural language query methods for extracting insights from LiDAR data.
- Case studies or examples showcasing the effectiveness of natural language queries in analyzing LiDAR-derived information.
4. Development of a Simple Chatbot Interface for Data Queries:
- Design and implementation of a user-friendly chatbot interface.
- Features and functionalities of the chatbot for querying digital data stored in the cloud.
- User experience considerations and user feedback from interface testing.
Requirements
Educational Qualifications:
- Qualified or partly qualified with a bachelor’s or master’s degree in computer science, engineering, data science, or a related field.
- Strong programming skills in languages such as Python.
Experience Required:
- Experience with machine learning libraries and frameworks, such as scikit-learn, TensorFlow, or PyTorch.
Knowledge, Skills & Abilities Required:
- Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
- Knowledge of software engineering principles and best practices, including version control and documentation.
- Passion for environmental sustainability and interest in applying machine learning to address water-related challenges.
- Excellent problem-solving and critical-thinking skills.
- Strong communication and collaboration skills.
- Data preparation and preprocessing: Assist in collecting, cleaning, and preprocessing datasets from various sources, including satellite imagery, remote sensors, and field surveys.
- Feature engineering: Engineer relevant features from raw data to improve model performance and interpretability.
- Model development: Develop, train, and evaluate machine learning models, including supervised and unsupervised learning algorithms, to solve specific research problems and objectives.
- Model deployment: Deploy machine learning models into production environments, ensuring scalability, reliability, and efficiency.
- Model optimization: Optimize machine learning models for performance, scalability, and resource efficiency, considering factors such as computational cost and model interpretability.
- Version control and documentation: Maintain version control of machine learning code and documentation. Document the machine learning process, methodologies, and results.
- Collaboration: Collaborate with interdisciplinary teams of researchers, scientists, and engineers to integrate machine learning solutions into ongoing research projects.
- Learning and development: Stay updated on the latest developments in machine learning techniques, tools, and technologies. Take initiative to learn new skills and technologies relevant to the field.
LANGUAGE PROFICIENCY:
- Excellent oral and written language skills in English, including effective listening and strong verbal and written communication abilities.
Benefits
This is a nationally hired consultancy; therefore, individuals with relevant abilities are encouraged to apply. IWMI offers a competitive monthly rate for this assignment. The duration of the contract will be for a period of five (05) months.
HOW TO APPLY: Apply for the position by following the application instructions at www.iwmi.org/jobs. We will be accepting applications through 24:00 (IST) on July 13, 2024 (applications will be reviewed on a rolling basis). Your application must include a CV, cover letter, and three (3) references, which may be contacted if you are shortlisted. Receipt of all applications will be acknowledged, but only short-listed candidates will be contacted.
IWMI believes that diversity powers our innovation, contributes to our excellence, and is critical for our mission. We offer a multi-cultural, multi-color, multi-generational and multi-disciplinary working environment. We are consciously creating an inclusive organization that reflects our global character and our commitment to gender equity. We, therefore, encourage applicants from all cultures, races, ethnicities, religions, sexes, national or regional origins, ages, disability status, sexual orientations, and gender identities.
Added 21 days ago
-
Updated 2 hours ago
-
Source:
cgiar.org
