Offer summary

Qualifications:

Experience with AWS services such as Sagemaker and Lambda., Proficiency in containerization using Docker and/or Kubernetes., Strong skills in Python for MLOps tasks including data preparation and model deployment., Familiarity with ETL pipelines and infrastructure tools like Terraform or Jenkins..

Key responsabilities:

Design and implement a restocking solution using AWS Batch and Docker Containers.

Build and automate model training, retraining, and validation pipelines.

Containerize code and environments for efficient deployment.

Run unit tests on production code to ensure quality and reliability.

We are a staffing solutions and IT Solutions company that provides you with a platform to find the right fit for your desired job profile. The employment situation is constantly shifting with the changing times, and we are here to ensure that you gather the workforce that compliments your long-term goals. We understand the struggle of the search for talent that accommodates the skills and qualifications for specific profiles, one that blends in with the theme of your organization. We aim to be the best available source for young talent to find their dream jobs, by helping them narrowing down their options to the most suitable work profiles available in the market. At RIG, we consistently work towards creating the latest technology that may not only simplify your work process but also provides you with the most cost-effective solutions. We work hard to make sure that your business strives in the market to be on the top in your field.

Job description

MLOps Engineer
Until 12/30/2022 with auto-renewal
Dallas, TX. Remote

Requirements:
MLOps engineer, responsible for design and implement a restocking solution using AWS Batch and Docker Containers.
Hands on experience containerizing code and environments with Docker and/or Kubernetes Experience building ETL Pipelines for Client Model Data Ingestion
Experience building automated Model Training/Retraining and Validation Pipelines
Strong experience with AWS Client stack (Sagemaker, Lambda, etc.)
Strong experience with python-based MLOps (data prep, model deployment, monitoring, etc.)
Modeling skills and experience with marketing use cases is a plus
Experience specifying infrastructure to be built using tools such as Terraform or Jenkins
Expertise in designing and running unit tests on production code

Required profile