EMW, Inc.
Computer & Network Security
MachineLearningEngineer(NS)
“Machine Learning Engineer (NS) at EMW, Inc.. Skills: Machine Learning, AI, Python, MLOps. Apply ML/AI techniques to new problems. Build, optimize, and maintain ML/AI models”
What You'll Achieve.
Deliver secure, reliable, and maintainable solutions; Validate and accept completed ML/AI modules against agreed functional, quality, and performance criteria
Industry & Context.
Apply ML/AI techniques to new problems; Identify issues in models and pipelines; Recommend and implement improvements; Apply data science techniques to new problems
NATO SECRET security clearance, Full Time On-Site, 100% Time On-Site, Air-gapped / restricted-network environments
What They're Looking For.
Must Have
NATO SECRET security clearance, 5+ years of hands-on experience building ML/AI solutions in Python, Foundations in machine learning concepts, Foundations in software engineering, Foundations in production-grade development practices, Proven experience designing, developing, optimizing, and maintaining end-to-end AI/ML pipelines, Track record in model evaluation and performance measurement, Experience applying and adapting pre-trained models, Solid experience with MLOps practices, Proficiency with CI/CD pipelines, Proficiency with DevOps best practices, Practical experience with containerization, Orchestration using Kubernetes, Experience with workflow orchestration tools, Experience building and maintaining REST APIs
Nice to Have
Experience building production-grade AI agent backends, Full-stack experience with TypeScript frameworks, Experience working in air-gapped / restricted-network environments
What You'll Do.
Apply ML/AI techniques to new problems
and maintain ML/AI models
and maintain supporting pipelines
Evaluate and monitor ML/AI system outcomes
Evaluate and monitor model performance
Define appropriate metrics and acceptance criteria
Identify issues in models and pipelines
Recommend and implement improvements
document programs/scripts
Refactor and maintain programs/scripts
Support ML development and deployment
Follow engineering standards
and maintainable solutions
Monitor progress and report status
Elicit requirements for ML/AI lifecycle practices
Select and implement appropriate lifecycle practices
Deploy automation for build/release processes
Define ML/AI modules for integration builds
Produce build definitions for each release
Validate and accept completed ML/AI modules
Apply data science techniques to new problems
Use specialized programming approaches
Identify and implement opportunities to improve training data
Identify and implement opportunities to improve features
Identify and implement opportunities to improve model performance
Build and maintain data pipelines
Support monitoring of emerging technologies
Contribute to internal reports
Contribute to technology roadmaps
Contribute to knowledge sharing
How You'll Work.
Team & Collaboration
Collaborate with teammates through code reviews; Collaborate with teammates through design reviews; Shared ownership of deliverables
Communication Scope
Report status; Communicate risks, blockers, and dependencies
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