Manager, ML Ops

Job not on LinkedIn

July 29

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Learneo

Education • Productivity • B2B

Learneo is a pioneering platform that focuses on building a collection of builder-driven businesses aimed at enhancing productivity and learning for everyone. By fostering an environment of decentralized entrepreneurial teams, it promotes innovation, collaboration, and the efficient delivery of educational resources. Committed to continuous growth, Learneo offers a wide range of educational tools and services, empowering individuals to learn and achieve their fullest potential in a dynamic and evolving online learning market.

📋 Description

•QuillBot is looking for a hands-on MLOps Manager to lead and scale our AI Engineering & MLOps function. •This role blends deep technical execution (60%) with team and cross-functional collaboration (40%). •You'll work closely with Research, Platform, Infra, and Product teams. •Own the full ML lifecycle: from training infra and experiment tracking to deployment, observability, and optimization. •Work closely with researchers to remove friction in training, evaluation, and finetuning workflows. •Guide and mentor a small, mature team of engineers (3–4) while still contributing as an individual contributor. •Drive performance optimization (latency, throughput, cost efficiency), model packaging, and runtime reliability. •Build robust systems for CI/CD, versioning, rollback, A/B testing, monitoring, and alerting. •Ensure scalable, secure, and compliant AI infrastructure across training and inference environments. •Collaborate with cloud and AI providers (e.g., AWS, GCP, OpenAI). •Contribute to other GenAI and cross-functional AI initiatives as needed. •Champion automation, DevOps/MLOps best practices, and technical excellence across the ML lifecycle.

🎯 Requirements

•5+ years of strong experience in MLOps, ML/AI Engineering. •Solid understanding of ML/DL fundamentals and applied experience in model deployment and training infra. •Proficient with cloud-native ML tooling (e.g., GCP, Vertex AI, Kubernetes). •Comfortable working on both training-side infra and inference-side systems. •Good to have experience with model optimization techniques (e.g., quantization, distillation, FasterTransformer, TensorRT-LLM). •Proven ability to lead complex technical projects end-to-end with minimal oversight. •Strong collaboration and communication skills — able to work cross-functionally and drive technical clarity. •Ownership mindset — comfortable making decisions and guiding others in ambiguous problem spaces.

🏖️ Benefits

•Competitive salary, stock options & annual bonus •Medical coverage •Life and accidental insurance •Vacation & leaves of absence (menstrual, flexible, special, and more!) •Developmental opportunities through education & developmental reimbursements & professional workshops •Maternity & parental leave •Hybrid & remote model with flexible working hours •On-site & remote company events throughout the year •Tech & WFH stipends & new hire allowances •Employee referral program •Premium access to QuillBot

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