MLOps Engineer, Machine Learning Infrastructure & CI/CD
Overview
You will own machine learning infrastructure and CI/CD pipelines, taking models from research to scalable production at Rivago infotech inc. You will design and maintain monitoring systems and infrastructure using Python, Google Cloud Platform, and IaC. You will work on cross-functional teams to automate pipelines and ensure model reliability. This role combines deep ML tooling expertise with production engineering, offering direct impact on enterprise ML deployments.
What You'll Do8
- 1Design and maintain CI/CD pipelines for machine learning models, automating build, test, and deployment processes.
- 2Build and manage infrastructure using IaC tools like Terraform to support scalable ML workloads on Google Cloud Platform.
- 3Implement and maintain monitoring systems for model performance, data drift, and system health in production.
- 4Deploy and version machine learning models using MLflow or similar tools, ensuring reproducibility and traceability.
- 5Collaborate with data scientists to containerize models using Docker and orchestrate with Kubernetes.
- 6Optimize pipeline performance for low latency and high throughput, targeting 5+ years of experience in production ML systems.
- 7Automate model retraining and deployment workflows, reducing manual effort and errors.
- 8Ensure security and compliance across ML infrastructure, implementing best practices for data handling and access control.
Requirements8
- 16-10 years of experience in MLOps, DevOps, or related fields, with a focus on machine learning infrastructure.
- 2Strong proficiency in Python for scripting, automation, and building ML pipelines.
- 3Hands-on experience with Google Cloud Platform services like Vertex AI, BigQuery, and Cloud Functions.
- 4Experience with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions.
- 5Proficiency in IaC tools like Terraform or Cloud Deployment Manager.
- 6Knowledge of ML tooling like MLflow, Kubeflow, or TensorFlow Extended.
- 7Experience with Docker and Kubernetes for containerization and orchestration.
- 8Familiarity with monitoring tools like Prometheus, Grafana, or Cloud Monitoring.
Salary Insight
$114 - $121k per year
Location
Required Skills
Similar open positions
Explore active roles that match your skills and interests.
Rivago infotech inc
VerifiedMLOps Engineer, ML Pipelines & CI/CD
You will own the design, deployment, and management of scalable machine learning pipelines in production, serving models that power enterprise systems. Your work integrates ML models with AWS, Kubernetes, and Terraform, ensuring reliability and automation. You'll collaborate with data scientists and software engineers to streamline model delivery, and drive governance and monitoring for model performance. This role stands out with its focus on owning the full MLOps lifecycle from data ingestion to model retraining.
Lorven Technologies, Inc.
VerifiedLead MLOps Engineer, Fraud Detection & GCP
You will lead the design and deployment of enterprise-scale fraud detection platforms, owning the ML lifecycle from model training to production. Your stack centers on Google Cloud Platform and Agentic AI Architecture, with a team of data scientists and platform engineers. You will set the MLOps roadmap and drive automation, making this role pivotal for fraud prevention at scale.
Compugra Systems
VerifiedLead MLOps Engineer Fraud Detection Platform
Own end to end ML deployment frameworks for enterprise scale fraud detection systems at Compugra Systems in Dallas Texas. Drive scalability reliability and governance while leading cross functional teams.
LTIMindtree
VerifiedMLOps Engineer - LTIMindtree Tampa
As an MLOps Engineer at LTIMindtree, you will own the deployment and lifecycle management of machine learning models across production environments for enterprise clients. You will work with a global team of data scientists and engineers to build and maintain CI/CD pipelines for ML workflows, ensuring reliability and scalability. This role offers the chance to shape MLOps standards in a consulting environment, collaborating with clients in Tampa and beyond.
Bain & Co.
VerifiedSenior AI/ML Engineer, LLMOps & RAG Systems
You build production inference, serving, and LLMOps infrastructure for Python-based ML systems, taking models from prototype to governed deployment. Bain's Private Equity Group Innovation team creates proprietary data and software products, and your work supports over 1,000 professionals across the investment lifecycle. You collaborate with Data Scientists, Data Engineers, and the Agent/AI squad to deliver reliable, observable ML systems. This hands-on role sets engineering standards and mentors mid-level engineers, with daily use of MLflow, Kubernetes, and Databricks.
Intellisoft Technologies
VerifiedAI/ML Architect, MLOps & Agentic AI
You will design and implement end-to-end machine learning systems at scale, owning the full ML lifecycle from data pipelines to model deployment and Agentic AI integration. You will work hands-on with Kubernetes, Docker, and AWS in a collaborative team of engineers and data scientists. This role stands out for its focus on production-grade MLOps and the chance to shape AI infrastructure in a fast-moving environment.