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Lead DevOps/MLOps Engineer

Remote in Reston, VA, US • Posted 2 hours ago • Updated 2 hours ago

Full Time

On-site

USD $120,000.00 - 160,000.00 per year

Fitment

Dice Job Match Score™

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Job Details

Skills

Machine Learning Operations (ML Ops)
FOCUS
Dashboard
Migration
Machine Learning (ML)
Image Management
Promotions
Orchestration
Amazon Web Services
Terraform
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Amazon SageMaker
DevOps
Workflow
Value Engineering
GPU

Summary

We're looking for a strong DevOps engineer who can help scale and operationalize our infrastructure as the platform grows. This is not a pure platform-architecture role - the focus is CI/CD, infrastructure automation, deployment reliability, observability, and GPU-oriented workload scaling.
What You'll Own

Improve CI/CD pipelines, deployment workflows, and release reliability
Standardize infrastructure and deployment patterns across environments
Improve observability through logging, metrics, tracing, dashboards, and rollout monitoring
Partner closely with backend engineering on:
- deployment strategies
- infrastructure automation
- environment consistency
- migration workflows
- possible Kubernetes migration efforts
Support ML-oriented infrastructure as a secondary responsibility:
- SageMaker workloads
- Ray clusters
- GPU scaling patterns
- distributed batch execution
- autoscaling behavior
- runtime/image management
- artifact delivery/versioning

The Kind of Problems You'll Work On

Deployment safety and rollback strategies
Infrastructure consistency across environments
Release automation and environment promotion flows
Autoscaling and runtime stability
GPU workload orchestration and scaling efficiency
Operational tooling that reduces friction for engineering teams

Stack

AWS
Terraform
Docker
Kubernetes
CI/CD systems
SageMaker
Ray
GPU compute infrastructure

You'll Probably Do Well Here If

You've operated production infrastructure at meaningful scale
You're strong in practical DevOps execution and operational reliability
You care about automation, observability, and deployment safety
You're comfortable improving developer workflows and infrastructure tooling
You've worked with distributed systems or GPU-oriented workloads before

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91123694
Position Id: 9b039338d52d6aa35b127fe3d1b02981
Posted 2 hours ago

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