Applied AI Scientist - LLMs & Voice

Our mission

We're making Africa the first cashless continent.

In 2017, over half the population in Sub-Saharan Africa had no bank account. That's for good reason—the fees are too high, the closest branch can be miles away, and nobody takes cards. Without access to financial institutions, people are forced to keep their savings under the mattress. Small business owners rely on lenders who charge extortionate rates. Parents spend hours waiting in line to pay school fees in cash.

We're solving this by building financial services that just work: no account fees, instantly available, and accepted everywhere. In places where electricity, water and roads don't always work, you can still send money with Wave. In 2017, we launched a mobile app in Senegal for cash deposit, withdrawal, and peer-to-peer and business payments. Now, we have millions of users across 9 countries and are growing fast.

Our goal is to make Africa the first cashless continent and that's where you come in...

How you'll help us achieve it

Wave is now the largest financial institution in Senegal and Côte d’Ivoire, with millions of users, growing rapidly year on year. And, we’re still in the early days of our product roadmap and potential impact on people’s everyday lives.

We're helping millions of customers across West Africa access financial services through mobile money, and great support is fundamental to that. We believe the future of customer support lies in machines handling boring repetitive tasks so humans can focus on high value interactions that require empathy and creativity

As an Applied AI Scientist on our Support Automation product team, you will:

• Be responsible for driving the quality of our automated support through evaluating and improving everything the team builds
• Bridge research and production, building agent systems that ship into real products.
• Contribute to autonomous voice and digital agents that power 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.

Key Details

• This is a fully remote role. Candidates must be based in one of our talent hub countries (US, UK, Spain, Kenya and Ghana) or in one of our operating markets in Africa including Senegal, Côte d'Ivoire, or Burkina Faso.
• Wave is a distributed team, and we fund up to three in-person get-togethers a year, in line with Wave's travel policy.
• Our salaries are competitive and are calculated using a transparent formula. For this role, depending on your level and location, we offer a salary between $167,00 - $227,900 USD, plus a generous equity package.
• Major benefits:
• 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.

Requirements

• 5+ years of experience in AI/ML experience
• Proven hands-on experience building with LLMs or AI systems (evaluation, RAG, embeddings, safety and guardrails etc.).
• Strong foundations in statistics and ML theory.
• Solid Python skills.
• Track record taking AI/ML systems from prototype to production and care deeply about reliability, performance, and scalability.
• Fluency with AI agents, with bonus points for deploying them as part of production systems
• Bonus points:
• 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