ML Ops Engineer-W2

Company: OORVI SYSTEMS INC
Location: Houston
Posted on: February 2, 2025

Job Description:

Hi All,

Are you ready to apply Make sure you understand all the responsibilities and tasks associated with this role before proceeding.

Good Morning,

We have an urgent position for the below mentioned requirement.

Title: ML Ops Engineer

Location: Remote

Duration: Long Term--W2

Note: LinkedIn Mandatory

Job Summary:

As an ML Ops Engineer, you will play a key role in integrating machine learning models into production environments. You will work closely with data scientists and engineering teams, ensuring that models are efficiently deployed, tested, and validated. This role requires strong knowledge of data science principles, machine learning workflows, and the ability to understand and troubleshoot code to ensure quality and performance at every stage of the model lifecycle.

You should be able to independently understand user stories from sprints and work autonomously with minimal supervision.



Key Responsibilities:

Model Deployment s Automation: Manage the end-to-end lifecycle of machine learning models, including deployment, validation, and monitoring using Kubernetes, Jenkins, and AWS
Collaboration with Teams: Work closely with data scientists, software engineers, and product teams to understand and implement machine learning
Code Understanding s Quality Assurance: Review, validate, and test Python- based machine learning code, ensuring adherence to coding standards and best practices. Participate in code reviews and provide constructive
Model Validation: Ensure proper validation of models before production deployment, including data preparation, testing, and optimization of machine learning
Performance Optimization: Optimize model performance, ensuring scalability and efficiency, particularly in cloud environments (AWS).
Documentation: Contribute to technical documentation, outlining deployment pipelines, model performance, and best
Continuous Integration/Continuous Deployment (CI/CD): Work with Jenkins for deployment automation and integrate code into CI/CD pipelines to ensure seamless, consistent delivery.



Required Qualifications:



Experience: 8-12+ years of experience working in machine learning, model development, and deployment.



Core Skills:

Strong foundation in data science
Expertise in machine learning techniques and libraries such as XGBoost and
scikit-learn (sklearn).
Proficiency in Python for data science and machine learning model
Hands-on experience with Kubernetes for deploying and scaling machine learning
Experience with AWS tools and cloud
Experience with Jenkins for automated testing and
Strong understanding of model deployment, validation, and monitoring in production
Experience in PR reviews, ensuring code quality, and adherence to coding
Experience with DASK for parallel computing and handling large
Familiarity with other AWS services like S3, Lambda, SageMaker, and
Strong communication skills and ability to work autonomously in a fast-paced, remote

Keywords: OORVI SYSTEMS INC, Sugar Land , ML Ops Engineer-W2, Engineering , Houston, Texas