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Principal MLOPs Engineer

Posted 5 months agoViewed

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💎 Seniority level: Principal, 10+ years with a Bachelor's degree or 8+ years with a Master's degree

📍 Location: USA

🔍 Industry: Multicloud solutions

🏢 Company: Rackspace👥 1001-5000💰 Private over 7 years ago🫂 Last layoff almost 2 years agoIaaSBig DataCloud ComputingCloud Infrastructure

🗣️ Languages: English

⏳ Experience: 10+ years with a Bachelor's degree or 8+ years with a Master's degree

🪄 Skills: LeadershipPythonApache HadoopGCPHadoopJavaKerasMachine LearningC++AlgorithmsData StructuresSparkTensorflowCommunication SkillsC (Programming language)

Requirements:
  • Proven experience in designing and implementing scalable ML inference systems.
  • Hands-on experience with deep learning frameworks like TensorFlow, Keras, or Spark MLlib.
  • Solid understanding of ML algorithms, natural language processing, and statistical modeling.
  • Strong knowledge of computer science concepts such as algorithms, distributed systems, and database management.
  • Effective problem-solving skills and critical thinking.
  • Experience in the Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
  • Expertise in public cloud services, specifically GCP and Vertex AI.
  • Recent proficiency in Java and knowledge of model optimization techniques.
Responsibilities:
  • Architect and optimize the existing data infrastructure to support machine learning and deep learning models.
  • Collaborate with cross-functional teams to align engineering solutions with business objectives.
  • Develop and operate cost-effective inference systems for a variety of models, including LLMs.
  • Provide technical leadership and mentorship for the engineering team.
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🏢 Company: Raft Company Website

  • 7+ years of relevant hands-on experience.
  • 5+ years experience with Docker and Kubernetes.
  • 5+ years experience supporting enterprise Cloud applications or infrastructure (AWS, Azure, etc.).
  • Solid understanding of Helm Charts.
  • Practical experience with Machine Learning on Kubernetes.
  • Experience managing clusters with GPU machines.
  • Experience building and maintaining machine learning platforms and pipelines.
  • Practical programming and scripting skills (Python preferred).
  • Strong communication skills, analytical thinking, and creative problem-solving.
  • Familiarity with modern software development practices including scrum/agile, Git, and DevOps.
  • Ability to obtain a Security+ certification within the first 90 days.

  • Deploy ML infrastructure.
  • Build MLOps pipelines.
  • Contribute to the development of a full-lifecycle ML platform.
  • Collaborate with a team to enhance operators' awareness of critical events.
  • Process large volumes of real-time data efficiently.

AWSDockerPythonSoftware DevelopmentAgileGitJavaKafkaKubernetesMachine LearningSCRUMAzureCommunication SkillsCollaborationCI/CDDevOpsAttention to detailComplianceScripting

Posted about 2 months ago
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