Position Details

Type Full-Time

Experience mid

Exp. Years 3+ years

Education Not specified

Category AI & Machine Learning

About this role

This role involves designing, building, and maintaining machine learning infrastructure and pipelines, primarily managing GPU workloads on Kubernetes within a government or defense environment.

Key Responsibilities

Design ML pipelines
Manage GPU workloads
Maintain infrastructure
Collaborate with data scientists
Ensure security compliance

Technical Overview

Focuses on ML pipelines, GPU workloads, Kubernetes, Docker, and cloud-native tools, with security clearance requirements.

Ideal Candidate

The ideal candidate is a mid-level ML Ops engineer with over 3 years of experience in building machine learning pipelines, managing GPU workloads on Kubernetes, and working with cloud-native tools. They should have experience with government or defense projects and hold or be able to obtain security clearances.

Must-Have Skills

3+ years experiencebuilding ML pipelinesPythonPyTorch or TensorFlowKubernetesGPU workloadsAirflowMinIO

Nice-to-Have Skills

DoD experienceComputer visionLarge imagery formatsGitHub repositoriesDocker

Tools & Platforms

KubernetesPyTorchTensorFlowAirflowMinIODocker

Required Skills

PythonPyTorchTensorFlowKubernetesAirflowMinIOGPU workloadsDocker

Hard Skills

PythonPyTorchTensorFlowKubernetesAirflowMinIOGPU workloadsContainerizationDevSecOpsCloud-native

Soft Skills

Analytical thinkingProblem-solvingCommunicationHands-on approachFast learnerTeamwork

Industry & Role

Industry Government / Public Sector / Technology

Job Function Develop and maintain machine learning infrastructure for government projects

Role Subtype AI & Machine Learning

Tech Domains Python, PyTorch, TensorFlow, Kubernetes, Docker, Machine Learning, DevSecOps, Cloud-native

Clearance & Visa

Clearance Required Active TS with ability to obtain and maintain SCI

Visa Sponsorship No

Keywords for Your Resume

ML Ops EngineerPythonPyTorchTensorFlowKubernetesAirflowMinIOGPU workloadsDockerDevSecOpscloud-nativeTS clearanceSCI clearancemachine learning pipelinesdistributed workloadsGPU clustersK8scontainer orchestrationfederally funded projectsgovernment

Deal Breakers

Lack of experience with Kubernetes or GPU workloads, No security clearance or ability to obtain TS/SCI, No experience with ML pipelines, Inability to work onsite in Tampa

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