MLOps Engineer

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

Key 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.