Lorven Technologies
Azure Data Engineer - Multiple Locations
Lorven Technologies, Dallas, Texas, United States, 75215
Hi,
Our client is looking for a
Azure Data Engineer for Long-term Project in Multiple locations
below is the detailed requirement.
Job Role: Azure Data Engineer with ML Experience
Location: Multiple Locations
Mode of Hiring: Long Term
Responsibilities:
Design the
data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scaleTake offline models data scientists build and turn them into a real machine learning production systemDevelop and deploy scalable tools and services for clients to handle machine learning training and inferenceIdentify and evaluate new technologies to improve performance, maintainability, and reliability of our clients' machine learning systemsApply software engineering rigor and best
practices to machine learning, including CI/CD, automation, etc.Support model development, with an emphasis on auditability, versioning, and data securityFacilitate the development and deployment of proof-of-concept machine learning systemsCommunicate with clients to build requirements and track progressQualifications:
10+ years experience in
Data Engineering space with full stack development, with hands-on experience in building machine learning production infrastructure (MLOps)Minimum 5+ year working experience streamlining the
development, deployment, and management of machine learning models in production environments.Mandatory experience working in
Databricks, Azure DevOps, and ML experience specifically in Databricks
(ML flow, Feature Store, working w/ the model registry, etc.)Experience building end-to-end systems as a Platform Engineer/ ML DevOps EngineerStrong software engineering skills in complex, multi-language systems. Fluency in Python, Go or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etcExperience working with cloud computing and database systemsExperience building custom
integrations between cloud-based systems using APIs .Experience on CICD pipelines orchestration experience - deploying machine learning solutions using DevOps principles is quite highExperience developing and
maintaining ML systems built with open source toolsFamiliarity with one or more
data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)Exposure to machine learning methodology and best practices
Our client is looking for a
Azure Data Engineer for Long-term Project in Multiple locations
below is the detailed requirement.
Job Role: Azure Data Engineer with ML Experience
Location: Multiple Locations
Mode of Hiring: Long Term
Responsibilities:
Design the
data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scaleTake offline models data scientists build and turn them into a real machine learning production systemDevelop and deploy scalable tools and services for clients to handle machine learning training and inferenceIdentify and evaluate new technologies to improve performance, maintainability, and reliability of our clients' machine learning systemsApply software engineering rigor and best
practices to machine learning, including CI/CD, automation, etc.Support model development, with an emphasis on auditability, versioning, and data securityFacilitate the development and deployment of proof-of-concept machine learning systemsCommunicate with clients to build requirements and track progressQualifications:
10+ years experience in
Data Engineering space with full stack development, with hands-on experience in building machine learning production infrastructure (MLOps)Minimum 5+ year working experience streamlining the
development, deployment, and management of machine learning models in production environments.Mandatory experience working in
Databricks, Azure DevOps, and ML experience specifically in Databricks
(ML flow, Feature Store, working w/ the model registry, etc.)Experience building end-to-end systems as a Platform Engineer/ ML DevOps EngineerStrong software engineering skills in complex, multi-language systems. Fluency in Python, Go or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etcExperience working with cloud computing and database systemsExperience building custom
integrations between cloud-based systems using APIs .Experience on CICD pipelines orchestration experience - deploying machine learning solutions using DevOps principles is quite highExperience developing and
maintaining ML systems built with open source toolsFamiliarity with one or more
data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)Exposure to machine learning methodology and best practices