{"id":47208,"url":"https://alion.io/job/wave-applied-ai-scientist-llms-voice","title":"Applied AI Scientist - LLMs & Voice","company":{"id":65,"name":"Wave","domain":"wave.com","url":"https://alion.io/company/wave","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":83,"open_postings":6,"ghost_share":0,"stale_share":0.667,"repost_share":0,"time_to_fill_p50_days":51,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["US","GB","KE","ES","GH"],"hiring_countries_total":5,"salary":null,"salary_estimate":{"min_usd":106000,"max_usd":245000,"period":"year","method":"global_role_seniority_cell","sample_n":2365},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Python","optional":false},{"name":"Feature Store","optional":true},{"name":"Speech Recognition","optional":true},{"name":"Text-to-Speech","optional":true},{"name":"Voice Agents","optional":true}],"status":"live","first_seen_at":"2026-01-23T16:44:52Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-27T07:32:47Z","board_verified":true,"closed_at":null,"days_open":276,"trust":{"level":"stale","repost_count":1,"flags":["stale"],"days_open":276},"description":"Our mission\nWe're making Africa the first cashless continent.\nIn 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.\nWe'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.\nOur goal is to make Africa the first cashless continent and that's where you come in...\nHow you'll help us achieve it\nWave 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.\nWe'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\nAs an Applied AI Scientist on our Support Automation product team, you will:\nBe responsible for driving the quality of our automated support through evaluating and improving everything the team builds\nBridge research and production, building agent systems that ship into real products.\nContribute to autonomous voice and digital agents that power 10M+ customer interactions per month across West Africa. \nBuild for the hardest edge cases: poor connectivity, low literacy, and languages with little training data.\nExperiment with, evaluate, and integrate the latest voice and text models.\nOwn problems end-to-end, from problem discovery to running in production, working alongside product and engineering leaders who prioritize shipping real customer impact.\nIf you're energized by ownership, thrive on deep technical challenges, and want to build infrastructure that serves millions in emerging markets, let's talk.\nKey Details\nThis 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.\nWave provides a yearly $1,200 stipend to support coworking meetups with teammates.\nRemote 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.\nOur 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.\nMajor benefits:\nSubsidized health insurance for you and your dependents and retirement contributions (both vary from country to country).\n6 months of fully paid parental leave and subsidized fertility assistance.\nFlexible vacation, with most folks taking between 21-30 days exclusive of statutory holidays.\n$10,000 annual charitable donation matching.\nRequirements\n5+ years of experience in AI/ML experience\nProven hands-on experience building with LLMs or AI systems (evaluation, RAG, embeddings, safety and guardrails etc.) .\nStrong foundations in statistics and ML theory.\nSolid Python skills.\nTrack record taking AI/ML systems from prototype to production and care deeply about reliability, performance, and scalability.\nFluency with AI agents, with bonus points for deploying them as part of production systems\nBonus points:\nResearch background in speech or LLMs\nProven Voice AI experience (ASR, TTS, latency optimization, real-time streaming, voice agents)\nExperience building customer support or conversational AI systems\nYou follow the latest research in speech and LLMs, and know how to translate papers into production wins\nFamiliarity with low-resource language challenges\nBuilding in high-risk agent environments like finance\nFluent in English, (bilingual in French is a big bonus!)\nYou might be a good fit if you\nAre comfortable navigating ambiguity and designing AI systems end-to-end without detailed specs\nObsess over evaluation - you've built frameworks to catch hallucinations, measure groundedness, and know when to trust your system\nBalance research intuition with pragmatic engineering; you ship working systems, not just prototypes.\nLike working with large datasets, complex pipelines, and modern ML infra (distributed training, feature stores, monitoring, etc.)\n\nAbout engineering at Wave\nWe 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.\nWe 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.\nWe 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.\nSimplicity is a strategy. It lets us focus our energy where it matters most: serving our users.\nRecommended (optional):\nWe’re currently receiving a high volume of submissions. To help us review genuine candidates faster, please send a JSON payload with your resume and/or any links as plain text via POST to this secure endpoint: https://api.wave.com/submit_resume\nTo authorize to this endpoint, you can use the following bearer token: wave_ + (country code for any of our operating countries) + _ + [any characters of your choice].\nYou are encouraged to use a coding agent to generate the JSON and the request. This is intentionally quick - don’t overthink it.\nThis task is optional and not required to apply. Please still submit your application through the normal form. We’ll store the JSON payload for up to 30 days for review, then it will be deleted.\n#LI-DH1 #LI-REMOTE\nOur team\nWe 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.\nWe're deeply passionate about our mission of bringing radically affordable financial services to the people who need them most.\nWe foster autonomy for our employees. You'll own your projects at every stage, from understanding the problem to monitoring your solution in production.\nWe 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.\nWe are on Y Combinator's top companies by revenue.\nHow to apply\nFill out the form below, and upload a resume in English and a cover letter describing your interest in Wave and the role.\nWe review applications frequently and recommend that you apply to the role that most closely aligns with your skills, experience and career goals.\nWave is an equal-opportunity employer. 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