Apply

Principal MLOPs Engineer (Canada)

Posted 2024-08-14

View full description

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

πŸ“ Location: Canada

πŸ” Industry: Multicloud solutions and technology services

🏒 Company: RackspaceπŸ‘₯ 1001-5000πŸ’° $ Private on 2017-09-11πŸ«‚ on 2023-03-27IaaSBig DataCloud ComputingCloud Infrastructure

πŸ—£οΈ Languages: English

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

πŸͺ„ Skills: LeadershipPythonApache HadoopGCPHadoopJavaKerasMachine LearningC++AlgorithmsData StructuresSparkTensorflowC (Programming language)

Requirements:
  • Proven track record in designing and implementing scalable ML inference systems.
  • Hands-on experience with deep learning frameworks such as TensorFlow, Keras, or Spark MLlib.
  • Solid foundation in machine learning algorithms, natural language processing, and statistical modeling.
  • Strong understanding of computer science concepts including algorithms and distributed systems.
  • Proficiency and recent experience in Java is required.
  • Experience in Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
  • Expertise in public cloud services, particularly GCP and Vertex AI.
  • Understanding of LLM architectures and model optimization techniques.
Responsibilities:
  • Architect and optimize existing data infrastructure for machine learning and deep learning models.
  • Collaborate with cross-functional teams to translate business objectives into engineering solutions.
  • Own development and operation of high-performance inference systems for various models.
  • Provide technical leadership and mentorship to the engineering team.
Apply

Related Jobs

Apply

πŸ“ Canada

πŸ” Machine Learning / Artificial Intelligence

  • Significant expertise in Machine Learning engineering.
  • Strong background in infrastructure related to ML.
  • Proven experience in building and scaling ML inference platforms in a production environment.

  • Architect, build, and optimize ML inference platform.
  • Focus on building Machine Learning inference systems.
  • Drive improvements to existing systems and processes.

LeadershipPythonSoftware DevelopmentArtificial IntelligenceMachine LearningCross-functional Team LeadershipCommunication SkillsAnalytical SkillsCollaboration

Posted 2024-11-07
Apply