Applied AI Engineer

Applied AI Engineer

Full-Time 48000 - 72000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Build AI models to revolutionise financial services for millions in Africa.
  • Company: Join Wave, a leading fintech on a mission to make Africa cashless.
  • Benefits: Competitive salary, equity package, health insurance, and flexible vacation.
  • Why this job: Make a real impact by solving everyday financial challenges for users.
  • Qualifications: 5 years of ML experience and strong Python skills required.
  • Other info: Fully remote role with travel opportunities to operational markets.

The predicted salary is between 48000 - 72000 ÂŁ per year.

Our mission is to make Africa the first cashless continent. In 2017, over half the population in Sub‑Saharan Africa had no bank account due to high fees and accessibility issues. We are solving this by building financial services that work without account fees, are instantly available, and accepted everywhere. 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.

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. 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.

  • 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 case: 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.

Key details: This is a fully remote role. Candidates must be based in one of our talent hub countries (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. Exceptions apply, but we’ve found this key to understanding our users and product. 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 $222,700, 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 ML experience.
  • Strong proficiency in Python and common ML libraries.
  • Solid theoretical foundation in statistics and ML.
  • Experience working with voice agents.
  • Proven hands‑on experience building with LLMs or NLP systems (prompt engineering, RAG, embeddings, fine‑tuning, etc.).
  • Experience taking ML models from prototype to production and care deeply about reliability, performance, and scalability.
  • Fluent in English; bilingual in French is a big bonus!

You might be a good fit if:

  • Are comfortable navigating ambiguity and designing ML systems end‑to‑end without needing extremely detailed requirements.
  • Understand the trade‑offs between cutting‑edge research and pragmatic engineering, and can choose the right tool for the job.
  • 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 on Y Combinator's top companies by revenue.

How to apply: Fill out the form below, and upload a resume in English and a cover letter describing your interest in Wave and the role. We review applications frequently and recommend that you apply to the role that most closely aligns with your skills, experience and career goals. Wave is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Applied AI Engineer employer: Wave Mobile Money

Wave is an exceptional employer dedicated to transforming financial services in Africa, offering a fully remote role for an Applied AI Engineer with competitive salaries and generous equity packages. Our vibrant work culture prioritises autonomy, innovation, and meaningful impact, while providing substantial benefits such as subsidised health insurance, flexible vacation, and a commitment to employee growth through hands-on project ownership. Join us in making a difference across West Africa, where your contributions will directly enhance the lives of millions.
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Contact Detail:

Wave Mobile Money Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Applied AI Engineer

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and ML. This is your chance to demonstrate what you can do beyond just a CV—make it pop!

✨Tip Number 3

Prepare for interviews by practising common questions and scenarios specific to AI engineering. Think about how you’d tackle real-world problems, especially in low-connectivity environments—this will impress the hiring team!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in our mission of making Africa cashless.

We think you need these skills to ace Applied AI Engineer

Machine Learning (ML)
Python
ML Libraries
Statistics
Voice Agents
Large Language Models (LLMs)
Natural Language Processing (NLP)
Prompt Engineering
Data Engineering
Model Deployment
Reliability Engineering
Performance Optimisation
Scalability
Bilingual in English and French

Some tips for your application 🫡

Tailor Your Resume: Make sure your resume speaks directly to the role of Applied AI Engineer. Highlight your experience with ML, Python, and any relevant projects that showcase your skills in building AI models and systems.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share why you're passionate about Wave's mission and how your background aligns with our goals. Be genuine and let your personality come through.

Showcase Your Problem-Solving Skills: In your application, emphasise your ability to navigate ambiguity and design ML systems end-to-end. We love candidates who can demonstrate their thought process and how they tackle challenges.

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for the role. We can’t wait to see what you bring to the table!

How to prepare for a job interview at Wave Mobile Money

✨Know Your Stuff

Make sure you brush up on your machine learning concepts, especially around voice agents and NLP systems. Be ready to discuss your hands-on experience with LLMs and how you've taken models from prototype to production.

✨Understand the Mission

Familiarise yourself with Wave's mission to make Africa cashless. Show that you understand the challenges faced in the region and how your skills can help solve real-world problems for users.

✨Show Your Problem-Solving Skills

Prepare examples of how you've tackled ambiguity in past projects. Highlight your ability to design ML systems end-to-end and how you've navigated trade-offs between cutting-edge research and practical engineering.

✨Be Ready to Collaborate

Wave values teamwork and autonomy. Think of instances where you've worked cross-functionally or helped unblock teammates. Emphasise your willingness to jump in wherever needed and your passion for solving meaningful problems.

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