Senior MLOps Engineer - Remote ML Pipelines

your Jared; Boston, Northern (MA, KY); Hybrid; USD 170,000 - 180,000; Full time

Benefits offered by this job

Stock options

Base salary transparency

Medical insurance plans with HSA

Dental and vision insurance

Unlimited PTO

Autonomy and upward mobility

Diversity and inclusion

Job summary

Zeitview is seeking a Senior MLOps Engineer I to turn ML models into reliable production services. You will own model registry, deployment pipelines, cloud infrastructure, and monitoring across multiple verticals, bridging R&D, software engineering, and DevOps.

You’ll collaborate with ML Scientists, Data Scientists, and Perception Engineers to translate experiments into scalable, observable systems, implement safer release practices, and ensure reproducibility with versioning and experiment

Qualifications

• Bachelor's degree in Computer Science, Software Engineering or related field with strong ML/AI focus.

Responsibilities

• Partner with Scientists: Translate experimental code into dependable, scalable production services.
• Cross-functional Collaboration with DevOps and Software Engineering on infrastructure requests and data pipelines.
• Model Registry, Deployment & Release Management: Maintain and improve model registry and deployment pipelines with safe release practices.
• Cloud Infrastructure & CI/CD: Build and maintain cloud infra and CI/CD pipelines for ML workloads.
• Monitoring, Drift & Reproducibility: Implement monitoring and observability for models and pipelines in production.
• Ongoing Maintenance & Platform Support: Keep deployed ML systems healthy with upgrades and retraining support.
• Standards & Documentation: Define conventions for model versioning and deployment promotion.

Skills

Python

MLOps

Cloud AWS

CI/CD

Kubernetes

Terraform

Model registry

Experiment tracking

Communication

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Git

AWS Console

Job description

Zeitview is seeking a Senior MLOps Engineer I to turn ML models into reliable production services. You will own model registry, deployment pipelines, cloud infrastructure, and monitoring across multiple verticals, bridging R&D, software engineering, and DevOps.

You’ll collaborate with ML Scientists, Data Scientists, and Perception Engineers to translate experiments into scalable, observable systems, implement safer release practices, and ensure reproducibility with versioning and experiment