Principal ML Ops Architect

1 month ago


Bengaluru, India Tetrahed INC Full time
Principal ML OpsArchitectResponsibilities:1.Strategic Leadership:a.Define and drive the overall ML Ops strategy and roadmap for theorganization aligning it with business objectives and technicalcapabilities.b. Oversee the designdevelopment and implementation of ML Ops platforms frameworks andprocesses.c. Foster a culture of innovationand continuous improvement within the ML Opsteam.2.Technical Architecture:a.Design and implement scalable reliable and efficient ML Opsarchitectures.b. Select and integrateappropriate tools technologies and frameworks to support the MLlifecycle.c. Ensure compliance with industrybest practices and standards for MLOps.3. TeamManagement:a. Lead and mentor a team of MLOps engineers and architects.b. Fostercollaboration and knowledge sharing among teammembers.c. Provide technical guidance andsupport to data scientists andengineers.4.Innovation and Research:a.Stay uptodate with emerging ML Ops trends andtechnologies.b. Research and evaluate newtools and techniques to enhance ML Opscapabilities.c. Contribute to thedevelopment of innovative ML Opssolutions.Minimum RequiredSkills:
  • 11 years ofexperience preferred.
  • Proven track record ofdesigning and implementing largescale ML pipelines andinfrastructure.
  • Experience with distributedcomputing frameworks (SparkHadoop)
Knowledge of graphdatabases and auto MLlibraries
  • Bachelors / Master sdegree in computer science analytics mathematicsstatistics
  • Strong experience in PythonSQL.
  • Solid understanding and knowledge ofcontainerization technologies (DockerKubernetes).
  • Proficient in Experience in CI/CDpipelines model monitoring and MLOps platforms (KubeflowMLFlow)
  • Proficiency in cloud platformscontainerization and ML frameworks (TensorFlowPyTorch).
Certifications in cloudplatforms or ML technologies can be aplus.
  • Extensive experience withcloud platforms (AWS GCP Azure) and containerization technologies(Docker Kubernetes).
  • Strongproblemsolving and analyticalskills.
  • Ability toplan execute and take ownership oftask.
KeywordsML Ops / MLOps Architect AzureDevOps DockerKubernetes TensorFlowMLFlow PipelineMachine Learning Platform Engineer DataScience Platform Engineer DevOps Engineer(with ML focus) AIEngineer DataEngineer Cloud Engineer (with MLfocus) Software Engineer (with MLfocus) Model DeploymentSpecialist MLOpsArchitect CI/CDPyTorch ScikitlearnCloud Computing BigData Azureo AzureMachine Learning GCPoVertex AI AWSo AmazonSageMaker

ml,ops,azure,devops,docker,kubernetes,tensorflow,pipeline,machinelearning,data science,devops practices,google cloudplatform,software engineers,modeldeployment,ci,cd,pytorch,scikit-learn,cloud computing,bigdata,gcp,vertex,aws



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