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Lead MLOps Engineer
Impress is hiring a Lead MLOps Engineer for its onsite team in Barcelona. The role involves designing and maintaining machine learning model deployment infrastructure on AWS and GCP, including with Kubernetes and Terraform. The person will lead the team and must have at least six years of experience in ML engineering, MLOps, or production ML platforms.
Information about Impress
- Official domain
- smile2impress.com
- Open jobs
- 48
Job details
The full description published by Impress.
Description de l’offre
🌟 Join Impress – Europe’s Leading Health-Tech Innovator! We believe everyone deserves a smile they’ll love 😁. As the largest Ortho clinic chain in Europe, we combine cutting-edge tech with expert care, revolutionizing invisible orthodontics since 2019. With 150+ clinics across 10 countries 🌍 and rapid growth, we’re improving lives worldwide. We are looking for an
- Lead MLOps Engineer to join our Onsite Team in Barcelona. 📢 Why we’re cool:
- Work with an international and multicultural team
- Competitive salary
- Teeth aligner and whitening benefits
- Collaborative work environment and positive culture
- Opportunities to grow within a fast-paced, innovative company and real start-up experience with big challenges
- Fresh fruits and healthy snacks at the office 🔥
What You'll Do
- Own the ML Platform : Design, build and maintain ML serving and deployment infrastructure across AWS and GCP.
- Manage Cloud Infrastructure: Multi-environment setup (dev, prelive, live) using Terraform and Terragrunt.
- Run ML on Kubernetes: Deployments, health checks, secrets management and observability.
- Optimize GPU Inference: Profiling, batching, model conversion (ONNX/TorchScript), Triton Server.
- Drive Cost Efficiency : Right-size compute, build scale-to-zero GPU strategies, own monthly infra spend and cost-per-inference metrics.
- Lead the Team: Define ownership areas, grow engineers technically, set platform direction.
- Bridge ML & Product: Work with researchers, PMs and clinical teams to take models from prototype to production. What We Are Looking For:
- 6+ years of experience in ML engineering, MLOps, or ML platform roles with production responsibility;
- Strong hands-on experience with cloud infrastructure
- AWS (Lambda, Batch, Step Functions, S3, EC2, ECS/EKS, DynamoDB, RDS) and/or GCP (Cloud Run, Artifact Registry);
- Proficiency with Infrastructure as Code
- Terraform and/or Terragrunt for managing multi-environment cloud deployments;
- Experience deploying and operating ML inference services in production (Triton Server, TorchServe, FastAPI, or equivalent);
- Experience with Docker
- multi-stage builds, image optimization, container registries;
- Strong understanding of GPU compute for ML workloads
- instance selection, cost optimization, inference profiling;
- Demonstrated ability to deliver end-to-end ML services from infrastructure provisioning to production deployment;
- Experience with event-driven architectures
- SNS, SQS, webhooks, or equivalent message-passing systems;
- Track record of quantifiable business impact
- cost reductions, automation rates, throughput improvements;
- Ability to lead and develop a small engineering team. Will be a plus:
- Experience training deep learning models (PyTorch, segmentation models, computer vision);
- Familiarity with model optimization techniques
- ONNX/TorchScript conversion, quantization, batching strategies;
- Experience with ArgoCD or other GitOps tooling for Kubernetes;
- Background in healthcare, dental-tech, or other regulated / precision-critical domains;
- Experience with Terragrunt for managing multi-account, multi-environment Terraform at scale;
- Hands-on use of AI coding tools (Cursor, Copilot, ChatGPT) to accelerate infrastructure and ML development. At Impress we cultivate a culture of inclusion and diversity. We celebrate our employees' individual strengths, views, and experiences and we encourage all candidates to apply, without regard to race, color, religion, gender identity, sexual orientation, age, national origin, disability, or any other fact o r 🌈💪
Requirements
- Au moins six ans d’expérience en ingénierie ML, MLOps ou plateformes ML en production
- AWS et/ou GCP
- Terraform et/ou Terragrunt
- Déploiement de services d’inférence ML en production
- Docker
- Calcul GPU pour les charges de travail ML
- Architectures événementielles
- Capacité à diriger et développer une petite équipe
Benefits mentioned
- Avantages liés aux aligneurs dentaires et au blanchiment
- Équipe internationale et multiculturelle
- Fruits frais et en-cas sains au bureau
- Environnement de travail collaboratif
Workplace
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