[Remote] Senior ML Engineer / MLOps Engineer

Note: The job is a remote job and is open to candidates in USA. EXL is seeking a highly capable Senior ML Engineer / MLOps Engineer with strong experience in building, deploying, and scaling machine learning systems in production. This role involves close collaboration with data scientists and stakeholders to operationalize ML models for business-critical use cases, ensuring scalability, reliability, and performance in production environments.ResponsibilitiesDesign, develop, and deploy end-to-end ML pipelines covering data ingestion, transformation, feature engineering, model training, evaluation, and production deploymentDeploy and scale ML models on cloud platforms such as AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions), ensuring robust and cost-efficient architecturesBuild and maintain CI/CD/CT pipelines using tools like GitHub Actions, Jenkins, or cloud-native services to automate model training, testing, and deploymentContainerize applications using Docker and orchestrate using Kubernetes, while managing infrastructure through Terraform or CloudFormationImplement model lifecycle management practices, including model registries, versioning, and feature stores (e.g., MLflow, Feast), and establish strong observability frameworks using Prometheus and GrafanaDevelop monitoring systems to track ML performance metrics, data drift, model drift, and overall model health, ensuring timely retraining and optimizationBuild scalable data pipelines using Airflow, Spark, and SQL, and work with orchestration tools such as Apache Airflow or AWS Step FunctionsCollaborate closely with data scientists to productionize ML models for real-time and batch inference, enable A/B testing where applicable, and ensure smooth delivery of client-facing solutionsProvide mentorship to junior engineers and drive adoption of best practices in MLOps and software engineeringSkillsStrong experience in ML Engineering / MLOps with demonstrated delivery of end-to-end ML solutions in production environmentsProficiency in Python and advanced SQL, along with hands-on experience in ML frameworks such as Scikit-learn, TensorFlow, and PyTorchSolid understanding of machine learning algorithms, evaluation techniques, performance metrics, and validation strategiesHands-on expertise in cloud platforms (AWS or GCP), containerization (Docker), orchestration (Kubernetes), and CI/CD tools (Jenkins, GitHub Actions)Familiarity with MLflow, Feast, Prometheus, Grafana, and modern model monitoring practices including data and model drift detectionStrong problem-solving, communication, and stakeholder management skills with the ability to work independently in fast-paced environmentsBachelor's degree in computer science, Engineering, or a related field preferredExperience with real-time ML serving frameworks (KFServing, Seldon, Ray Serve), A/B testing, and experimentation platformsExposure to media, subscription, or recommender systems, along with knowledge of experiment design and causal inferenceCompany OverviewEXL is a provider of Transformation and Outsourcing services to Global 1000 companies in multiple industries It was founded in 1999, and is headquartered in New York, New York, USA, with a workforce of 10001+ employees. Its website is http://www.exlservice.com.Company H1B SponsorshipEXL has a track record of offering H1B sponsorships, with 1 in 2025, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.