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Company

Criterion Systems · 1 day ago

Senior Machine Learning Engineer

United States

Full-time

Remote

Senior Level

$147K/yr - $150K/yr

7+ years exp

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Cloud ComputingCyber Security

Senior Management

No H1B

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Responsibilities

Develop, train, test, and deploy ML models to production with robust monitoring and logging

Study and transform data science prototypes, select suitable data sets, and conduct data collection and modeling

Perform statistical analysis and tune hyper-parameters to enhance model performance

Automate work-flows for data collection, model training, and deployment

Implement continuous integration/continuous deployment (CI/CD) pipelines for ML projects

Monitor models in production and optimize performance over time

Work with data scientists to transition models from development to production

Document processes and provide knowledge transfer to other team members or teams

Evaluate and apply new tools and technologies to enhance ML operations (MLOps) practices

Lead customer communications and project presentations related to ML development

Coordinate with a peer ML Engineer on tasks and provide subject matter expertise to subordinate ML Engineers

Collaborate with cross-functional engineering and operations teams to deliver solutions

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

ML model developmentTensorFlowPyTorchMLOps principlesPythonDockerKubernetesAWS SageMakerAzure MLRBashProject documentationMicrosoft Office 365Agile environmentAWS Certified Solutions ArchitectMicrosoft Certified Azure Solutions Architect ExpertGoogle Cloud Professional Cloud Architect

Required

Experience in developing and deploying ML models at scale

Proficiency with ML frameworks such as TensorFlow, PyTorch, or similar

Experience implementing MLOps principles, including version control and CI/CD

Familiarity with infrastructure automation tools (e.g., Docker, Kubernetes)

Experience with cloud services implementing APIs for model deployment (e.g., AWS SageMaker, Azure ML)

Strong programming skills in Python, R, Bash, and/or other related languages for automation

Ability to clearly communicate/present technical issues and status to customers

Ability to create project documentation (e.g., SOP) and user guidance

Proficient with Microsoft Office 365 applications, specifically Word, Excel, PowerPoint, Outlook, OneDrive, Teams, and SharePoint

Experience working in an agile environment, coordinating across multiple teams

Ability to execute in a remote work environment

US Citizen or US Work Authorization

Preferred

Experience with Federal government customers preferred

AWS Certified Solutions Architect (Highly Desired)

Microsoft Certified Azure Solutions Architect Expert (Highly Desired)

Google Cloud Professional Cloud Architect

7 years of technical experience and a Bachelor’s Degree in Computer Science, Information Management (IM), Information Technology, Engineering, or equivalent; IT Solutions management experience preferred.