• Research AI technologies for current and future products • Design, develop, test, deploy, and maintain demo and production software • Monitor and improve current ML processes • Develop software to quickly and effectively collect training data • Improve the iteration time between prototype to end-user testing • Convert prototype software projects into demos and production software

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As an Applied AI Scientist on our Support Automation product team, you'll: - Bridge research and production, building AI models and agent systems that ship into real products. - Architect, evaluate, and optimize autonomous voice and digital agents powering 10M+ customer interactions per month across West Africa. - Build for the hardest edge cases: poor connectivity, low literacy, and languages with little training data. - Experiment with, evaluate, and integrate the latest voice and text models. - Own problems end-to-end, from problem discovery to running in production, working alongside product and engineering leaders who prioritize shipping real customer impact. If you're energized by ownership, thrive on deep technical challenges, and want to build infrastructure that serves millions in emerging markets, let's talk. Our stack (prior experience is a strong plus, but not required): - Backend: Python 3 (+ mypy) - API layer: GraphQL - Android frontend: Kotlin/Jetpack - iOS frontend: Swift/SwiftUI - Web frontend: TypeScript/React - Database: Postgres/CockroachDB - Infrastructure: GCP/Terraform - Orchestration: Kubernetes Qualifications - 5+ years of experience in AI/ML engineering - Strong Python and backend engineering skills - Solid foundation in statistics and ML theory - Proven hands-on experience building with LLMs (prompt engineering, RAG, embeddings, fine-tuning, agent orchestration etc.) - Track record taking ML models from prototype to production and care deeply about reliability, performance, and scalability. - Fluency with AI coding agents, with bonus points for deploying them as part of production systems Requirements - Research background in speech or LLMs - Proven Voice AI experience (ASR, TTS, latency optimization, real-time streaming, voice agents) - Experience building customer support or conversational AI systems - You follow the latest research in speech and LLMs, and know how to translate papers into production wins - Familiarity with low-resource language challenges - Fluent in English (bilingual in French is a big bonus!) Benefits - This is a fully remote role. Candidates must be based in one of our talent hub countries (US, Canada, UK, Spain, Kenya and Ghana) or in one of our operating markets in Africa including Senegal, Côte d'Ivoire, or Burkina Faso. - Wave provides a yearly $1,200 stipend to support coworking meetups with teammates. - Remote team members are expected to travel to our operational markets (e.g. Senegal or Côte d'Ivoire) at least once a year. - Our salaries are competitive and are calculated using a transparent formula. For this role, depending on your level and location, we offer a salary up to $227,900, plus a generous equity package. - Subsidized health insurance for you and your dependents and retirement contributions (both vary from country to country). - 6 months of fully paid parental leave and subsidized fertility assistance. - Flexible vacation, with most folks taking between 21-30 days exclusive of statutory holidays. - $10,000 annual charitable donation matching.

• Design, develop, and deploy Agentic AI systems and Generative AI solutions • Build and implement RAG and Information Retrieval pipelines for real-world use cases • Develop and integrate Large Language Models into production systems • Perform model evaluation, experimentation, and continuous improvement • Optimize model performance, scalability, and inference efficiency • Develop AI solutions using Python and modern ML/AI frameworks • Work with cloud platforms to deploy and manage AI workloads • Collaborate with engineering and product teams to translate requirements into AI-driven solutions • Apply prompt engineering techniques to improve LLM outputs • Maintain documentation and best practices for AI model development and deployment

• Design & build AI microservices (Python/FastAPI) that our core SaaS offering – EB360 (PHP/MySQL) – consumes via secure APIs • Prototype, evaluate, and operationalize LLMs (Bedrock, Hugging Face, frontier models) and classical ML for summarisation, autofill, validation, and agentic querying • Implement RAG pipelines: document ingestion, embedding generation, vector search, context packaging, and guardrails (prompt injection defence, PII redaction) • Document processing: OCR (Textract), NER (Comprehend/LLM), schema mapping, confidence scoring, and human-in-the-loop review for Due Diligence Questionnaires • Build secure, scalable data flows: S3 + Glue/Lambda/Step Functions; integrate with the data warehouse and EB360 data stores • Own production quality: testing, observability, tracing, model evaluation, A/Bs, latency budgets, error handling, and rollback plans • Apply secure-by-default practices (IAM least privilege, KMS, Secrets Manager, audit logs), contribute to SOC 2 controls (access, change, incident) • Partner with Product, Engineering, Client Success, and Data Engineers to scope, deliver, and iterate • Use/evangelise Cursor/Windsurf/Kiro for productivity; write internal docs, patterns, and reusable components. • Transform Ethixbase360’s data landscape into a strategic asset, enabling smarter decisions, faster innovation, and stronger client outcomes.