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DevOps / Machine Learning Engineer

  • Ireland
  • EUR 68.0 Hourly
  • Contract
  • Discipline:
  • Ref: 49968
Jelena Colic
Jelena Colic
Principal Consultant
jelena.colic@nicollcurtin.com+353 1 584 6856
Your experience as an ML engineer and your appetite for a new challenge is what we are looking for. The role positions you as a member of our fast paced and integrated group and will be involved in the full end-to-end process through analysis, planning, design, development, quality and implementation of the solutions. It is a dynamic environment requiring strong social skills, superb communication skills, a strong team mentality, superb attention to detail and a sense of ownership.
The Experience We're Looking For
  • You will utilise your experience working in large-scale, sophisticated systems development initiatives.
  • Significant experience working on AI/ML teams giving you exposure and understanding of the entire machine learning lifecycle.
  • Experience using CI/CD tools like Jenkins, uDeploy or Concourse to establish CI/CD pipelines to deploy code and services to AWS preferably (or similar Cloud Provider), familiarity with IAM roles and policies and other security related artefacts, certificates etc…
  • Hands-on experience using AWS Services especially related to data and analytics - S3, EC2, Lambda, Glue, SNS, SQS for example
  • Demonstrated experience in deploying data pipeline and OLTP systems in AWS; using platforms like RDS/Postgres and/or data warehousing tools like Snowflake
  • Experience maximising tools like EC2 and EKS to run compute for API hosting on AWS ideally
  • Hands-on experience in assisting with (EDA) and feature engineering, Deployment, Tuning, Monitoring, Measurement and Retraining using ML infrastructure and MLOps in the Cloud (AWS preferred).
The Skills You Bring
  • A dedication to your craft and experience in software development, deployment, API development and UI development
  • Exceptional SQL skills and experience performing complex data analysis on multiple Data Platforms (Snowflake, RDS/Postgres, DynamoDB)
  • Working with Orchestration/DAGS tools (Airflow, Prefect, Luigi, Kubeflow or equivalent)
  • API development using Java (Springboot) and/or Python microservices infrastructure and deployment using containerisation (Docker) and container-orchestration systems such as Kubernetes
  • Your understanding of Model Development and Scoring (inference)
  • Your technical leadership skills and ability to communicate with a highly diverse peer group, both verbally and in written communications.
  • Your leadership skills, which enable you to lead several projects concurrently, collaborating with multiple teams and coordinating dependencies to deliver high quality AI/ML solutions.
Nice to have or have an interest in learning;
  • Experience with Cloud service provider ML ecosystem such as AWS SageMaker, Azure ML and MLOps platform such as MLFlow, ModelOp, Seldon or equivalent
  • Experience with AWS and Azure AI ecosystems such as Textract, Comprehend, Kendra, Cognitive Services, etc

Apply for this job

We are an inclusive organisation and actively promote equality of opportunity for all with the right mix of talent, skills, and potential. We welcome all applications from a wide range of candidates. Selection for roles will be based on individual merit alone.

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DevOps / Machine Learning Engineer

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  • EUR 68.0 Hourly
  • Contract
Your experience as an ML engineer and your appetite for a new challenge is what we are looking for. The role positions you as a member of our fast paced and integrated group and will be involved in the full end-to-end process through analysis, planning, design, development, quality and implementation of the solutions. It is a dynamic environment requiring strong social skills, superb communication skills, a strong team mentality, superb attention to detail and a sense of ownership.
The Experience We're Looking For
  • You will utilise your experience working in large-scale, sophisticated systems development initiatives.
  • Significant experience working on AI/ML teams giving you exposure and understanding of the entire machine learning lifecycle.
  • Experience using CI/CD tools like Jenkins, uDeploy or Concourse to establish CI/CD pipelines to deploy code and services to AWS preferably (or similar Cloud Provider), familiarity with IAM roles and policies and other security related artefacts, certificates etc…
  • Hands-on experience using AWS Services especially related to data and analytics - S3, EC2, Lambda, Glue, SNS, SQS for example
  • Demonstrated experience in deploying data pipeline and OLTP systems in AWS; using platforms like RDS/Postgres and/or data warehousing tools like Snowflake
  • Experience maximising tools like EC2 and EKS to run compute for API hosting on AWS ideally
  • Hands-on experience in assisting with (EDA) and feature engineering, Deployment, Tuning, Monitoring, Measurement and Retraining using ML infrastructure and MLOps in the Cloud (AWS preferred).
The Skills You Bring
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  • Exceptional SQL skills and experience performing complex data analysis on multiple Data Platforms (Snowflake, RDS/Postgres, DynamoDB)
  • Working with Orchestration/DAGS tools (Airflow, Prefect, Luigi, Kubeflow or equivalent)
  • API development using Java (Springboot) and/or Python microservices infrastructure and deployment using containerisation (Docker) and container-orchestration systems such as Kubernetes
  • Your understanding of Model Development and Scoring (inference)
  • Your technical leadership skills and ability to communicate with a highly diverse peer group, both verbally and in written communications.
  • Your leadership skills, which enable you to lead several projects concurrently, collaborating with multiple teams and coordinating dependencies to deliver high quality AI/ML solutions.
Nice to have or have an interest in learning;
  • Experience with Cloud service provider ML ecosystem such as AWS SageMaker, Azure ML and MLOps platform such as MLFlow, ModelOp, Seldon or equivalent
  • Experience with AWS and Azure AI ecosystems such as Textract, Comprehend, Kendra, Cognitive Services, etc
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