MLOps Engineer

TheRole:
We areactively seeking a highly skilled MLOps Engineer to become anintegral part of our dynamic BF AI team. As we continue to innovateand drive forward in the realm of artificial intelligence werecognize the critical role that MLOps plays in ensuring theseamless deployment management and optimization of machine learningmodels. Join us in our pursuit of excellence as we harness thepower of AI to solve complex challenges and make a meaningfulimpact. If you are passionate about MLOps and eager to contributeyour expertise to a collaborative and forwardthinking environmentwe invite you to apply and be a part of our journey towardscuttingedgeinnovation.

Responsibilities:

• Designand implement infrastructure for deploying and managing ML modelsmainly focused on AWS services. This involves choosingorchestration tools for automating the MLworkflow.
  
• Containerize models toensure consistency and portable deployment across environments.
  
• Setup monitoring and trackingsystems to track the health of ML models in production.
  
• Automate the process of deploying MLmodels from dev to prod.
  
• Modelsversion control.
  
• Datasets versioncontrol.
  
• Collaborate with datascientists AI engineers and data engineers to understand the modelsand their requirements.
  
• Document theML workflows including deployment procedures monitoring practicesand retraining strategies.
  
• Implementsecurity measures to protect sensitive information used in MLmodels and during deployment.
  
• Ensuredata privacy regulations are adhered to throughout the MLlifecycle.
  
• Develop monitoringdashboards to visualize model performance and identify potentialissues proactively.

Requirements:

• Bacheloror Masters degree in ComputerScience.
  
• Experience of at least 5years in DevOps and MLOps.
  
• Strongunderstanding of machine learning concepts algorithms andtechniques.
  
• Proficiency in machinelearning libraries/frameworks such as TensorFlow PyTorch orscikitlearn.
  
• Experience in modeldevelopment training evaluation andoptimization.
  
• Ability to translatemachine learning models into productionreadycode.
  
• Deep knowledge of AWS servicesrelevant to machine learning such as Amazon SageMaker AWS LambdaAWS Glue AWS Step Functions AWS Batch and AmazonEMR.
  
• Familiarity with AWS storage anddatabase services such as Amazon S3 AmazonRDS.
  
• Expertise in containerizationtechnologies such as Docker and container orchestration withKubernetes.
  
• Proficiency in managinginfrastructure as code using tools like AWS CloudFormation orTerraform.
  
• Experience in continuousintegration and continuous deployment (CI/CD) pipelines for machinelearning models.
  
• Ability to monitorand troubleshoot production machine learning systems ensuring highavailability scalability andperformance.
  
• Understanding of DevOpsprinciples and practices including automation version control andcollaboration.
  
• Excellentcommunication collaboration and problemsolvingskills.
• AWS certifications relevant to machinelearning and operations such as AWS Certified Machine LearningSpecialty AWS Certified DevOps Engineer Professional or AWSCertified Solutions Architect Professional would be highlybeneficial

WakapiWeb