Roles & Responsibilities
- Data Exploration & Analysis: Collect, clean, and preprocess data from various sources. Perform exploratory data analysis (EDA) to uncover patterns and trends that support program interventions.
- Model Development & Deployment: Design, develop, and implement production-ready machine learning models.
- AI Systems Development: Develop and maintain retrieval-augmented systems, implement robust unit tests, and refactor existing codebases for improved performance.
- API Development for Model Serving and Data Processing: Design and implement APIs to facilitate efficient model deployment and data handling, ensuring seamless integration with existing systems.
- Data Visualization & Reporting: Create compelling visualizations, dashboards, and detailed reports to communicate insights to both technical and non-technical stakeholders.
- MLOps & Deployment: Handle end-to-end model deployment, including monitoring and maintenance in production environments. Implement CI/CD pipelines for ML models.
- Research & Innovation: Stay current with the latest developments in AI/ML, conduct R&D to improve methodologies, and implement cutting-edge solutions where appropriate.
Requirements and Experience
- Advanced degree in Data Science, Computer Science, Statistics, Mathematics, Software Engineering, Computer Engineering or a related field
- 4+ years of experience in data science and machine learning engineering.
- Strong programming proficiency in Python for AI/ML development, including data science libraries (NumPy, pandas, scikit-learn)
- Experience with deep learning frameworks (TensorFlow, PyTorch) and ML mod deployment
- Demonstrated experience with generative AI and large language models, including RAG systems and vector search implementations
- Experience with front-end technologies (React) and RESTful API development.
- Experience with MLOps tools (Docker, Kubernetes), CI/CD pipelines, and cloud platforms (AWS, GCP, Azure)
- Strong knowledge of SQL and NoSQL databases, including vector databases (eg. Quadrant, Pinecone, Weaviate)
- Expertise in data visualization tools (Tableau, Power BI) and advanced pr engineering techniques
- Proficiency with version control systems (Git) and data pipeline/ETL process.
- Strong analytical thinking and problem-solving abilities with a full-stack mindset.
- Outstanding communication and training skills for both technical and non-technical audiences
- Experience in participatory research within last-mile communities is an advantage.
- Self-motivated team player with the ability to manage multiple priorities
