We are hiring: MLOps Engineer – 07-August-2026 US Remote

Hiring Organization: MLOpsFlow Dynamics

Client ID: 942QMTR

Job ID: 837LKPV

Role Overview

MLOpsFlow Dynamics is looking for a systems-focused, highly analytical, and technically brilliant MLOps Engineer to join our remote-first AI infrastructure team. In this full-time role, you will be the backbone of our AI lifecycle, responsible for designing, automating, and scaling the pipelines that take machine learning models from research to production. We value expertise in Kubernetes, cloud infrastructure, and CI/CD for AI. Whether you are an experienced MLOps engineer or a talented fresher looking for a supportive environment to build your career in infrastructure automation, we offer a mentorship-rich culture where your contributions will directly impact our production scalability and deployment reliability.

Key Responsibilities

• Design and implement end-to-end automated machine learning pipelines (CI/CD/CT).
• Scale and manage model deployment infrastructure on cloud platforms (AWS, GCP, or Azure).
• Monitor production model performance, drift, and latency, implementing automated alerts and triggers.
• Build and maintain feature stores and model registries to streamline team collaboration.
• Optimize infrastructure costs and resource utilization for high-compute training and inference jobs.
• Collaborate with data scientists to package and containerize models for reliable, reproducible deployment.
• Debug complex production issues related to model serving, networking, or infrastructure scalability.
• Participate in peer code reviews and architectural planning to maintain engineering excellence.
• Contribute to the continuous improvement of internal MLOps tools, orchestration scripts, and testing frameworks.
• Document infrastructure design, deployment workflows, and operational best practices.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
• Strong proficiency in Python and solid experience with containerization technologies (Docker, Kubernetes).
• Experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, AWS SageMaker, or Azure ML).
• Understanding of CI/CD pipeline principles and infrastructure-as-code (Terraform or CloudFormation).
• Familiarity with version control systems like Git.
• Excellent communication skills and the ability to work effectively in a remote, distributed team.
• A proactive, problem-solving mindset and a passion for infrastructure automation.
• Freshers with strong academic foundations in systems or data engineering projects are encouraged to apply; we provide extensive mentorship.
• Reliable high-speed internet connection for consistent, professional virtual collaboration.

Preferred Skills

• Experience with GPU management and optimization for model training/inference.
• Knowledge of distributed computing frameworks (Spark, Ray).
• Experience with monitoring and observability stacks (Prometheus, Grafana, ELK).
• Understanding of security best practices in AI deployment.
• Experience with database systems (SQL/NoSQL) and feature stores.

What We Offer

• Competitive Annual Salary: $268,450.
• 100% remote flexibility from any location in the United States.
• Comprehensive health, dental, and vision insurance packages.
• Retirement savings plan with company matching contributions.
• Generous Paid Time Off (PTO), including holidays and personal wellness days.
• Structured career development, mentorship, and support for professional certifications.
• A highly collaborative, inclusive, and mission-driven engineering culture.

Employment Details

Workplace Type: Remote

Location: United States (US)

Job Type: Full-Time

Employment Type: FULL_TIME

Employer Address: 600 MLOpsWay, Suite 400, San Jose, CA 95110

Freshers Can Apply: Yes

Standard Application Notice

MLOpsFlow Dynamics is an equal opportunity employer. We value diversity and are committed to creating an inclusive culture for all employees. All hiring decisions are based on merit, qualifications, and the business needs of the organization. Please submit your application using the form below.