EXL

Analyzes business data and runs outsourced operations

Senior ML Ops Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeGurugram, Haryana, IndiaNo salary listed

About the Job

Requirements

Relevant experience in an ML Engineering or MLOps role with end-to-end understanding of ML-based solution design and architecture, development, implementation, and deployment.
Meet standard MLOps Level 2 requirements for CI/CD and CT pipeline automation.
Strong hands-on experience writing production-ready, scalable code using advanced SQL and Python.
Hands-on experience with at least one cloud stack: AWS, Azure, or GCP.
Ability to work independently hands-on.
A bachelor's degree from a Tier I or Tier II college is preferred.

Responsibilities

Actively own and manage client deliverables.
Design solution architectures and pipelines for ML applications.
Create ML prototypes, design ML systems, and develop automated ML application pipelines covering data collection, processing, cleaning, and transformation while ensuring scalability, correctness, and maintainability.
Implement model evaluation and model and data validation tools and techniques, including schema validation and evaluation metrics.
Develop and deploy CI/CD-based automated ML application pipelines covering collection, processing, cleaning, and transformation, with a CT component for a continuous feedback loop for retraining.
Set up feature stores, integrate pipelines, configure automated triggering, deliver models continuously, serve models via APIs, and monitor models.
Productionize models and make them available as APIs or microservices.
Promote a practice of unifying system development and system operations.
Thoroughly quality-check outputs and provide analytics-driven insights and next steps.
Perform statistical analysis and fine-tune models using test results.
Understand client data and the different platforms used by the client.
Contribute to problem solving and mentor junior team members.

Job description: Senior ML Ops Engineer Experience: 4-6 years Job Location: Gurgaon (Hybrid) Shift Timing: 1:00PM IST – 10:30 PM IST Skills/ Qualifications Required: Relevant experience in ML Engineering/ ML Ops role with an end-to-end understanding of ML based project’s solution design & architecture, development, implementation & deployment Should fulfill all the standard MLOps level 2 requirements for CI/CD + CT pipeline automation Strong grasp & hands on experience with production ready scalable code using SQL (advance) and Python Hands-on experience in working on any of the of cloud stacks: AWS/ Azure/ GCP Good communication skills Can work hands-on independently. Bachelor’s degree from Tier I/II colleges preferred Job Responsibilities Actively own & manage client deliverables. Design solution architectures and pipelines for ML applications. Create ML prototypes, design ML systems, develop automated ML application pipelines (across data collection, processing, cleaning, transformation etc. aspects) under the constraints of scalability, correctness, and maintainability. Implement model evaluation and model + data validation tools/ techniques such as schema validation, evaluation metrics etc. Develop and deploy fCI/CD based automated ML application pipelines (collection, processing, cleaning, transformation etc.) along with the CT component for continuous feedback loop for re-training. Strong skills in Feature store setup, Pipeline Integration, Automated triggering, Model Continuous Delivery, Model Serving (via APIs) & Model Monitoring Responsible for productionizing and making the models available as APIs / micro services. Promote a practice of unifying system development (Dev) and system operations (Ops) Ensure output’s thorough quality check & provide analytics driven insights and next steps. To perform statistical analysis and fine-tune models using test results. Understand data and different platforms used by the client. Actively contribute towards problem solving & mentor juniors in the team

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1999

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