Sr. ML Ops Engineer

About The Company:

iLink is a Global Software Solution Provider and Systems Integrator, delivers next-generation technology solutions to help clients solve complex business challenges, improve organizational effectiveness, increase business productivity, realize sustainable enterprise value and transform your business inside-out. iLink integrates software systems and develops custom applications, components, and frameworks on the latest platforms for IT departments, commercial accounts, application services providers (ASP) and independent software vendors (ISV). iLink solutions are used in a broad range of industries and functions, including healthcare, telecom, government, oil and gas, education, and life sciences. iLink’s expertise includes Cloud Computing & Application Modernization, Data Management & Analytics, Enterprise Mobility, Portal, collaboration & Social Employee Engagement, Embedded Systems and User Experience design etc.

 

What makes iLink Systems' offerings unique is the fact that we use pre-created frameworks, designed to accelerate software development and implementation of business processes for our clients. iLink has over 60 frameworks (solution accelerators), both industry-specific and horizontal, that can be easily customized and enhanced to meet your current business challenges.

Requirements

Roles & Responsibilities :

1. Ensure reliability and cost saving. Scale the proof of concept product to enterprise grade application with all the required components for reliability, scalability, monitoring and security.
2. Suggest and implement the best practices from Software engineering to ML workflow to ensure CI/CD, reproducibility and quick delivery cycle.
3. Lead and drive the deployment of ML models, life cycle management and monitoring of Machine Learning(ML) and Deep Learning (DL) models in in all stages leading to production
4. Be a subject matter expert on DevOps practices, CI/CD and Configuration Management with assigned engineering team
5. Automate and streamline ML operations and processes.
6. Build and maintain tools for deployment, monitoring, and operations. Also troubleshoot and resolve issues in development, testing, and production environments
7. Operate and maintain systems supporting the provisioning of new clients, applications, and features
8. Work to improve Data scientist and Data engineer productivity and delivery speed by enabling them to be more self-sufficient with automated operational processes.
9. Successfully devise and implement strategies to ensure ML heavy systems operate with high accuracy in Production and adapt to discovered needs.
10. Collaborate with Data Scientists, Data Engineers, ML Engineers, cloud platform and application engineers to create and implement cloud policies and governance for ML/DL model life cycle

Benefits

• Competitive salaries​
  
• Medical, Dental, Vision Insurance
  
• Disability, Life & AD&D Insurance
  
• 401K With Generous Company Match
  
• Paid Vacation and Personal Leave
  
• Pre-Paid Commute Options
  
• Employee Referral Bonuses
  
• Performance Based Bonuses
  
• Flexible Work Options & Fun Culture
  
• Continuing Education Reimbursements
  
• In-House Technology Training