Senior MLOps Engineer: Scalable AI Pipelines & Inference

Fundamental; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Salary + equity

Health coverage

Parental leave

Relocation support

Inclusive culture

Job summary

Fundamental is seeking an experienced MLOps Engineer in the United States to build and operate scalable ML pipelines, serving infrastructures, and automated deployment workflows. You will advance low-latency inference and robust production readiness across data pipelines, feature stores, and observability tooling.

You’ll collaborate with cross-functional teams to implement CI/CD, A/B testing, and scalable architectures while optimizing GPU usage and cloud resources for enterprise-scale

Qualifications

• 5+ years of MLOps/DevOps experience.
• Experience with ML platforms MLflow or WandB.
• Experience with model serving frameworks for low-latency inference.
• Experience building data pipelines for training and inference.
• Kubernetes on AWS, GCP, or Azure.
• Infrastructure as code (Terraform, Helm, GitOps).
• Proficient in Python, Bash, and Go.

Responsibilities

• Develop and manage scalable ML pipelines, CI/CD workflows, and orchestration.
• Design and implement model serving infrastructure (TorchServe, TensorFlow Serving, Triton).
• Develop scalable inference architectures with ultra-low latency.
• Implement A/B testing, canary releases, and rollback capabilities.
• Develop logging, alerting, and monitoring for model development and reliability.
• Improve GPU usage, autoscaling, and resource allocation.
• Design and maintain feature stores and scalable data pipelines.

Skills

MLOps

Python

Go

Bash

Software design

Education

Bachelor’s or Master’s degree in CS

Tools

MLflow

WandB

TorchServe

TensorFlow Serving

Kubernetes

Terraform

Helm

GitOps

OpenTelemetry

Prometheus

Job description

Fundamental is seeking an experienced MLOps Engineer in the United States to build and operate scalable ML pipelines, serving infrastructures, and automated deployment workflows. You will advance low-latency inference and robust production readiness across data pipelines, feature stores, and observability tooling.

You’ll collaborate with cross-functional teams to implement CI/CD, A/B testing, and scalable architectures while optimizing GPU usage and cloud resources for enterprise-scale