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MLOps Engineer Vector

3 months ago

Barrington, United States Appodeal Full time
Job DescriptionJob DescriptionSalary:

We are seeking a talented MLOps Engineer to join our Vector team in Barcelona.


Responsibilities:

  • Provision of ML AWS resources and infrastructure
  • Developing MLOps pipelines leveraging the Amazon AWS  platform and its features
  • Developing ML-oriented CI/CD pipelines
  • Deploying machine learning models in production
  • Help customers tackle challenges on a scale using distributed training frameworks 
  • Using and writing Terraform libraries for infrastructure deployment
  • Maintaining infrastructures and environments of all types, from dev to production
  • Security monitoring and administration


Requirements: 

  • Over 2 years of experience in MLOps
  • Master's or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience
  • Ability to design and implement cloud solutions and to build MLOps pipelines (entire ML project lifecycle, including data management, experimentation, model training, deployment,  and monitoring) on AWS  in production
  • Experience with one or more MLOps Frameworks like Kubeflow, MLFlow, SageMaker, DataRobot, Airflow, Dagster, etc. 
  • Fluency in Python, a good understanding of Linux, and knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc
  • Experience with DevOps concepts, CI/CD pipelines, and data security measures, along with expertise in cloud platform architecture
  • Knowledge of fundamental computer science concepts including common data structures and algorithms.
  • Monitor the MLOps tools/approaches landscape to actively identify solutions for various domain problems
  • AWS CloudFormation or Terraform templates for configuring AWS services
  • Ability to understand tools used by data scientists and experience with software development and test automation
  • Excellent English language skills
  • Ability to collaborate effectively with diverse teams

 

Nice to have:

  • ML certification (AWS ML Specialty or similar)
  • GCP or Azure knowledge (DevOps/MLOps)
  • Working knowledge with Snowflake, BigQuery, and/or Databricks 
  • Experience with Docker and Kubernetes
  • Working knowledge of some Vector Databases (OpenSearch, Qdrant, Weaviate, LanceDB, etc)
  • Experience with one or more large language models Frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex.