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Senior MLOps Engineer
RecruityTalentSenior MLOps Engineer designing and building MLOps platforms with a recruitment agency in Bulgaria. Collaborating with data scientists and engineers to ensure efficient machine learning operations.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in MLOps and ML Engineering, with a strong focus on AWS SageMaker, CI/CD workflows, and automation. Proven ability to collaborate with cross-functional teams and establish best practices in the ML lifecycle.
Highest-signal resume keywords
MLOpsAWS SageMakerCI/CD WorkflowsPythonTerraform
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
MLOpsML EngineeringAWS SageMakerPythonTerraformContainerizationDockerKubernetes
Soft Skills
Exceptional Communication SkillsSolution-Oriented Mindset
Tools & Technologies
AWS Cloud Services
Industry Keywords
ML LifecycleAutomationInfrastructure OptimizationObservability
Tech Stack
Tools & technologiesAWSCloudDockerKubernetesPythonTerraform
About the role
Key responsibilities & impact- Design and build our central MLOps Platform covering the complete ML lifecycle
- Architect robust CI/CD workflows and self-service capabilities
- Partner with Data Scientists, ML Engineers, and Infrastructure teams
- Establish and evangelize MLOps best practices across the organization
- Optimize infrastructure costs and enhance observability
Requirements
What you’ll need- 5+ years of experience in MLOps, ML Engineering, or DevOps
- Deep hands-on expertise with AWS SageMaker AI
- Strong proficiency in AWS cloud services, Python, and Terraform
- Solid understanding of the ML lifecycle and experience with containerization (Docker, Kubernetes)
- Exceptional communication skills
- Solution-oriented mindset with a passion for automation
Benefits
Comp & perks- Health insurance
- Professional development training
- Flexible work arrangements