Senior ML - MLOps Engineer
March 19
Description
• Design, develop, and deploy ML-powered systems • Maintain and improve such systems over time • Work closely with ML researchers to make sure the systems are functioning correctly and utilize efficient tooling • Work closely with the infra team to maintain the stability of the systems, identify and help address possible issues with underlying environments
Requirements
• 3 years of experience in software engineering • Good knowledge of Python and its ecosystem, specifically related to ML applications and their deployment (e.g. knowing how to take a model developed by researchers & convert it into a live deployment) • Understanding of microservices and common architectural patterns used alongside them • Experience using any REST framework (FastAPI preferably, but anything similar will do) • Familiarity with Linux and its ecosystem of CLI tools • Experience with writing containerized applications using Docker • Experience with any testing framework • Understanding of DevOps principles (CI/CD, infrastructure-as-code) • Experience with deploying any ML-based app • willingness to learn and being open to new tools/approaches/tech stacks • Good communication skills • Effective communication in English • Understanding the general computational requirements of common ML algorithms • Experience using (one of) k8s/docker-compose/any major cloud provider Would be a plus: • Understanding observability, metrics, alerts • Data engineering skills • Any prior MLE/ML research experience • Experience with any MLOps tools (like MLFlow, Pachyderm, KubeFlow, DVC, etc) • Familiarity with kubectl for debugging issues with k8s-based deployments
Benefits
• Market competitive salary • Small but highly skilled, technically savvy and passionate team • Open, honest and inclusive culture • Unlimited vacations and sick days • Benefits&perks
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