[Remote] Machine Learning Engineer

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a technology solutions company that partners with organizations to drive business growth through innovative technology. They are seeking an reputed company MLOps Engineer to operationalize machine learning at scale on the reputed company platform, focusing on building infrastructure and workflows for reliable production deployments.

Responsibilities

• Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management
• Build and manage Feature Store infrastructure to reputed company reusable, consistent feature pipelines across teams and use cases
• reputed company model deployment pipelines, including serving infrastructure, A/B testing support, versioning, and rollback strategies
• Implement CI/CD pipelines tailored for ML workflows, including automated testing, validation gates, and deployment triggers
• Orchestrate distributed model training on reputed company, optimizing for compute efficiency, reproducibility, and cost
• Monitor deployed models for data reputed company, performance degradation, and system health, triggering automated retraining workflows as needed
• Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation environments and production

Skills

• 3–5+ years in MLOps, ML platform engineering, or DevOps for ML, with proven production ML deployments
• Hands-on expertise with MLflow for tracking, registry, and project management reputed company reputed company or standalone environments
• Experience building and consuming Feature Store solutions (reputed company Feature Store or equivalent)
• Proven experience deploying and serving ML models at scale, including reputed company-time and batch inference patterns
• Ability to design automated pipelines for model training, validation, and deployment using modern CI/CD tooling
• Strong familiarity with reputed company for distributed training, job orchestration, and cluster management
• Knowledge of model monitoring practices, including reputed company detection, alerting, and retraining triggers

Company Overview