Applied AI Scientist - LLMs & Voice

Wave Mobile Money

United States

Remote

USD 167,000 - 228,000

Full time

2 days ago
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Benefits offered by this job

Subsidized health insurance
Retirement contributions
6 months parental leave
Fertility assistance
Flexible vacation (21–30 days)
$10,000 annual charitable donation

Job summary

Wave Mobile Money is seeking an Applied AI Scientist for its Support Automation team. In this role, you will drive the quality of automated support, bridge research and production, and help scale AI agents across West Africa where 10M+ customer interactions occur each month.

You will tackle edge cases with limited data and connectivity, building production-ready models. Join a distributed team working in a fully remote capacity with scope across multiple markets.

Qualifications

  • 5+ years of experience in AI/ML.
  • Hands-on experience building with LLMs or AI systems (evaluation, RAG, embeddings, 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; bonus points for deploying them as part of production systems

Responsibilities

  • 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.

Skills

AI/ML experience
LLMs
Python
Reliability
AI agents
English fluency

Job description

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

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
    • You follow the latest research in speech and LLMs, and know how to translate papers into production wins
    • Familiarity with low-resource language challenges
    • Building in high-risk agent environments like finance
    • Fluent in English, (bilingual in French is a big bonus!)
You might be a good fit if you
  • Are comfortable navigating ambiguity and designing AI systems end-to-end without detailed specs
  • Obsess over evaluation – you've built frameworks to catch hallucinations, measure groundedness, and know when to trust your system
  • Balance research intuition with pragmatic engineering; you ship working systems, not just prototypes.
  • Like working with large datasets, complex pipelines, and modern ML infra (distributed training, feature stores, monitoring, etc.)
About engineering at Wave

We care about the big picture. We don’t hire engineers to just ship tickets. We hire them to solve problems. That means caring deeply about outcomes, understanding context, and jumping in wherever something’s broken, even if it’s technically “not your area.” When we see problems, inefficiencies, or opportunities to make something better, we act. We dig into operational issues, clarify fuzzy product specs, or step into unfamiliar code to help unblock teammates.

We move as fast as possible. Speed matters. It lets us try things quickly, get feedback early, and course-correct while it’s cheap. So we write small PRs. We aim for MVPs. We leave TODOs and file follow-ups. We don’t over-perfect v1. That said, we’re building a financial product. Some things—like money movement, correctness, or security—deserve more caution.

We like boring technology. We favor tools that are reliable, well-understood, and easy to debug. This keeps us focused on solving meaningful problems instead of wrestling with unpredictable infrastructure. If a new technology helps us move faster, build safer, or solve a real need, we’ll consider it. But we don’t adopt tools just because they’re new—we adopt them because they’re right.

Simplicity is a strategy. It lets us focus our energy where it matters most: serving our users.

Our team
  • We have a rapidly growing in-country team in Senegal, Côte d'Ivoire, Mali, Burkina Faso, The Gambia, Uganda, Niger, Sierra Leone, and Cameroon plus remote team members spread across the world.
  • We're deeply passionate about our mission of bringing radically affordable financial services to the people who need them most.
  • We foster autonomy for our employees. You'll own your projects at every stage, from understanding the problem to monitoring your solution in production.
  • We raised the largest Series A in Africa in 2021. Our world-class investors, include Founders Fund, Sequoia Heritage, Stripe, Ribbit Capital, Y Combinator, and Partech Africa.
  • We are onY Combinator's top companies by revenue.

Wave is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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