MLOps Engineer

Company Overview and Culture

EXL (NASDAQ: EXLS) is a global analytics and digital solutions company that partners with clients to improve business outcomes and unlock growth. Bringing together deep domain expertise with robust data, powerful analytics, cloud, and AI, we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on creating value from data for driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquartered in New York, our team is over 40,000 strong, with more than 50 offices spanning six continents. For information, visit

For the past 20 years, EXL has worked as a strategic partner and won awards in its approach to helping its clients solve business challenges such as digital transformation, improving customer experience, streamlining business operations, taking products to market faster, improving corporate finance, building models to become compliant more quickly with new regulations, turning volumes of data into business opportunities, creating new channels for growth and better adapting to change. The business operates within four business units: Insurance, Health, Analytics, and Emerging businesses.

Job Description

We are seeking a highly skilled and experienced MLOps Engineer to join our organization EXL. As an MLOps Engineer, you will play a crucial role in developing and implementing machine learning operations processes and infrastructure to support our data science initiatives.

Responsibilities:

1. Develop and maintain end-to-end machine learning operations (MLOps) pipelines for deploying, monitoring, and scaling machine learning models.

2. Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems.

3. Design and implement automated testing frameworks for ML models to ensure accuracy, reliability, and performance.

4. Optimize model deployment processes by leveraging containerization technologies such as Docker or Kubernetes.

5. Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management.

6. Monitor deployed ML models in production environments to identify performance issues or anomalies.

7. Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.

8. Stay up-to-date with the latest advancements in MLOps toolkits, frameworks, best practices, and industry trends.

Requirements:

1. Bachelor’s degree in computer science or a related field; advanced degree preferred.

2. Minimum 5 years of experience working as an MLOps Engineer or similar role within a data-driven organization.

3. Experience with Kubernetes and Kubeflow is mandatory.

4. Strong understanding of machine learning concepts and algorithms.

5. Proficiency in Python developing ML pipelines/scripts.

6. Experience with popular MLOps toolkits such as Kubeflow Pipelines, TensorFlow Extended (TFX), MLflow, etc., is essential.

7. Solid knowledge of containerization technologies like Docker and Kubernetes for deploying ML models at scale.

8. Familiarity with cloud platforms like AWS/Azure/GCP for building scalable infrastructure solutions is highly desirable

9. Experience with version control systems like Git/GitHub for managing code repositories

10. Excellent problem-solving skills with the ability to analyse complex technical issues related to ML model deployments.

What we offer

EXL Analytics offers an exciting, fast paced and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world class analytics consultants.

You can expect to learn many aspects of businesses that our clients engage in. You will also learn effective teamwork and time-management skills - key aspects for personal and professional growth

Analytics requires different skill sets at different levels within the organization. At EXL Analytics, we invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques.

We provide guidance/ coaching to every employee through our mentoring program wherein every junior level employee is assigned a senior level professional as advisors

The experience at EXL Analytics sets the stage for further growth and development in our company and beyond

Base Salary Range Disclaimer: The base salary range represents the low and high end of the EXL salary range for this position. Actual salaries will vary depending on factors including but not limited to: location and experience. The base salary range listed is just one component of EXL's total compensation package for employees. Other rewards may include bonuses, a Paid Time Off policy, and many region-specific benefits.