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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in ML/AI engineering with a focus on fine-tuning language models, optimizing production AI systems, and mentoring junior engineers. Proficient in Python and TypeScript, with a strong understanding of evaluation-driven development and production deployment.
Highest-signal resume keywords
ML/AI Engineering ExperienceLLM Fine-TuningProduction AI System OptimizationPython ProficiencyBilingual in French and English
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
LLM Fine-TuningRAGEmbeddingsRegression TestingProduction AI Systems MonitoringSoftware Engineering FundamentalsTestingCIObservabilityOn-Device Model Deployment
Soft Skills
Execution-FocusedPragmaticAutonomousCuriosityTeam Spirit
Industry Keywords
Language ModelsDatasetsEvaluation HarnessesAI FeaturesCost OptimizationLatencyQualityAI Trade-OffsDocumentationMentoring
Tech Stack
Tools & technologiesPythonTypeScript
About the role
Key responsibilities & impact- Train, fine-tune, and evaluate proprietary language models, including small models running on-device
- Curate and maintain datasets, golden sets, and evaluation harnesses
- Ship model updates to production and measure their impact
- Own the health of production AI features across quality, cost, and latency
- Detect silent regressions and debug AI incidents end to end
- Maintain models, prompts, and pipelines as tooling and APIs evolve
- Partner with product managers and engineers on new AI use cases
- Build rapid, evidence-based prototypes and provide evaluation, cost, and latency data
- Explain AI trade-offs to non-technical colleagues
- Document work and mentor junior engineers and interns on AI topics
- Work alongside the CTO and engineering squads, owning the AI workstream for a product area
Requirements
What you’ll need- 3–5 years of experience in ML/AI engineering, with models or AI features shipped and operated in production
- Hands-on experience with LLM fine-tuning, RAG, embeddings, and evaluation methods, including golden sets, LLM-as-a-judge, and regression testing
- Experience monitoring and optimizing production AI systems for cost, latency, and quality
- Strong software engineering fundamentals, including testing, CI, and observability
- Proficiency in Python and the ability to work across a TypeScript product codebase
- Experience with small language models (SLMs) and on-device/on-premises model deployment is a strong plus
- Execution-focused, pragmatic, product-minded, and autonomous
- Naturally rigorous, with a strong instinct for evaluation-driven development
- Genuine curiosity about the fast-moving AI landscape
- Strong team spirit and a clear sense of priorities in a fast-moving scale-up
- Alignment with Mendo's values: Learning, Innovation, Excellence, Kindness, and Transparency
- Excellent command of French and English, both technically and professionally
Benefits
Comp & perks- BSPCE (equity) under our Series A policy
- Hybrid model with two days in the office and three days remote
- A learning environment with a team passionate about new technologies and generative AI
- A stimulating workplace with a young and supportive culture
- A meaningful mission: helping make AI accessible and impactful for everyone
