# Lead MLOps Platform Engineer – Distributed Training & Kubeflow

- Link: https://accel-dna.com/jobs/lead-mlops-platform-engineer-distributed-training/
- Published: 2026-10-24T08:00:00+00:00
- Author: Umar Mahmud

## Opportunity Overview

**Location:** 100% Remote (United States)
**Employment Type:** Full-Time Direct-
Hire via Accel DNA**Compensation Range:** $180,000 – $220,000 Base + Equity**Hiring
Agency:** Accel DNA – Premier Frontier Data & AI Talent Partner

Construct internal developer platforms for automated model experimentation, distributed
fine-tuning, and governed artifact tracking across AI research squads.

## Key Responsibilities:

 * Architect and maintain scalable MLOps platforms using Kubeflow, MLflow, and cloud-
   native Kubernetes operators.
 * Implement standardized CI/CD pipelines automating data validation, distributed
   model training, and automated canary deployment.
 * Manage feature stores, model registry governance, and lineage tracking for audit
   compliance.
 * Reduce model iteration cycle time from weeks to hours by providing self-service
   GPU experiment environments.

## What You Bring:

 * 6+ years of software/platform engineering with 3+ years dedicated to MLOps platforms.
 * Expertise in Kubernetes architecture, Argo Workflows, Docker, and infrastructure-
   as-code (Terraform).
 * Familiarity with PyTorch distributed training launchers (Torchrun) and cloud 
   storage architectures.
 * Strong focus on developer experience (DevEx) and internal tooling ergonomics.

## How to Apply:

Interested in exploring this opportunity? Submit your profile or portfolio directly
to [contact@accel-dna.com](https://accel-dna.com/jobs/lead-mlops-platform-engineer-distributed-training/contact@accel-dna.com)
or apply through [https://accel-dna.com/contact-us/](https://accel-dna.com/contact-us/).