yubo - Staff ML Engineer
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Requirements
• You have 8–10 years of experience in ML / Data, including work on large-scale datasets (datasets of hundreds of gigabytes) . • You have strong expertise in modern ML frameworks (TensorFlow or PyTorch or JAX). • You are highly proficient in Python (data ecosystem). • You have deep knowledge of neural networks and LLMs. • You understand ML systems end-to-end (data → training → deployment → monitoring). • You have strong experience in production ML systems, not only research. • You demonstrate strong product sense and can align models with business needs. • You are pragmatic and impact-driven (not purely research-oriented). • You are able to explain complex ML topics clearly (strong pedagogy). • You operate well under ambiguity and can structure complex problems. • You bring technical leadership and influence without authority.
Responsibilities
• ML SYSTEMS & DELIVERY • Deliver end-to-end ML use cases (recommendation, safety algorithms, etc.). • Ensure production readiness, scalability, and long-term maintainability. • Balance speed of delivery with robustness and reliability . • ML LIFECYCLE & RELIABILITY • Define and improve the full ML lifecycle (training, deployment, monitoring, iteration). • Establish KPIs and monitoring standards to track model performance over time. • Ensure continuous alignment with product and safety objectives . • PLATFORM & STANDARDIZATION • Contribute to the “ML as a Platform” strategy (tools, workflows, reusable components). • Define scalable standards for ML development across teams. • Enable self-service ML capabilities . • LEGACY & ADVANCED USE CASES • Take ownership of legacy models and realign them with current business needs. • Improve, retrain, and integrate them into modern pipelines. • Define standards for LLM usage (moderation, recommendation). • Explore and implement advanced ML approaches where relevant . • CROSS-FUNCTIONAL LEADERSHIP • Partner with Data Engineering, MLOps, Backend Platform, and Product teams. • Act as a bridge between ML, platform, and business stakeholders. • Bring technical leadership and structure to ML practices across the organization. • OUR TECHNICAL ENVIRONMENT / ML SCOPE • ML frameworks: PyTorch • Languages: Python (data stack) • Core topics: Neural networks, LLMs, data sampling • Use cases: Recommendation systems, safety algorithms, moderation • Ecosystem: Data Engineering, MLOps pipelines, Backend Platform • Deliver an end-to-end ML use case to validate impact and execution. • Audit and improve lifecycle management of existing ML models. • Refactor and retrain at least one legacy safety model. • Define and implement a reusable OCR standard as a platform component. • Establish standards for LLM usage in moderation and recommendation systems. • Contribute to defining the ML platform strategy and operating model. • Shift the organization from “deploy & forget” to reliable, measurable ML systems at scale. • THE RECRUITMENT PROCESS • Phone screen with a Talent Acquisition Manager • Interview with Mikael (Head of Platform Engineering) • Technical case study • Cultural fit assessments
Benefits
• A highly competitive salary range as well as equity in the company • A highly flexible remote work policy, 2 days at the office per month, with monthly team events. • We also cover fees for external professional events and meetups (Android Makers, etc…) • Great health insurance coverage for both you and your family by Alan, fully paid for by Yubo ! • Numerous benefits for parents: additional parental leave, easy access to nurseries and daycare facilities in France. • OUR APPROACH TO PRIVACY & SAFETY • As part of your role, you may handle tools and features involving personal data. We expect all employees to demonstrate strong awareness of privacy and safety issues, and to actively support our Privacy & Safety by Design efforts. • Here’s how we live our mission every day: • You own the impact: Step up, adapt, and make it matter • Unconventionally Smart: Hack with intent, borrow smart, build better • Be Bold & Resilient: Raise your head, break barriers, keep moving forward • One team, one mission: No egos, no passengers, just shared wins • Trust & Flexibility: Our hybrid model calls for only two office days a month; the rest is up to the rhythm that works best for you. • Culture is central at Yubo, hence the numerous benefits: • Cool Workplace: enjoy our amazing Parisian office and our many hybrid work options • Team Activities: participate in get-togethers, events, and team-building activities • Family-Friendly: we support parents with childcare options and family-friendly policies • Wellness Programs: benefit from comprehensive health insurance, wellness programs, sports classes, and mental well-being initiatives
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