About this role
Job Responsibilities:
- Model Deployment and Management:
- Drive ML prototypes into production ensuring seamless deployment and management on cloud at scale.
- Monitor real-time performance of deployed models, analyze data, and proactively address performance issues.
- Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability.
- Collaboration and Integration:
- Collaborate with DevOps engineers to manage cloud compute resources for ML model deployment and performance optimization.
- Work closely with ML scientists, software engineers, data engineers, and other stakeholders to implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated deployment.
- Innovation and Continuous Improvement:
- Stay updated with the latest advancements in MLOps technologies and recommend new tools and techniques.
- Contribute to the continuous improvement of team processes and workflows.
- Share knowledge and expertise to promote a collaborative learning environment.
- Development and Documentation:
- Build software to run and support machine-learning models.
- Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes.
- Participate in fast iteration cycles and adapt to evolving project requirements.
- Business Solutions and Strategy:
- Propose solutions and strategies to business challenges.
- Collaborate with Data Science team, Front End Developers, DBA, and DevOps teams to shape architecture and detailed designs.
- Mentorship:
- Conduct code reviews and mentor junior team members.
- Foster strong interpersonal skills, excellent communication skills, and collaboration skills within the team
Other facts
About EXL
Choosing a digital partner is about more than capabilities — it’s about collaboration and character.
Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments.
At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations.
Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale.
Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact.
We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition.
At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward.
For more information, visit www.exlservice.com.
What you'll do
- The Senior ML Operations Engineer will drive ML prototypes into production, ensuring seamless deployment and management on the cloud. They will also monitor real-time performance, troubleshoot issues, and collaborate with various teams to implement best practices for MLOps.
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