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Senior MLOps Engineer – SRE, DevOps
PrideLogicSenior MLOps Engineer focusing on ML infrastructure and SRE for efficient deployment and operation of ML workloads. Collaborating on innovations to improve model serving, reliability, and cost efficiency.
Tech Stack
Tools & technologiesAWSKubernetes
About the role
Key responsibilities & impact- Build and operate model and inference serving infrastructure
- Own the ML deployment lifecycle
- Operate agentic and LLM workloads in production
- Build reproducible, automated ML pipelines
- Extend infrastructure-as-code to ML systems
- Operate GitOps for ML workloads
- Run ML and AI workloads on multi-tenant Kubernetes
- Own ML reliability and observability
- Drive ML cost efficiency
- Use agentic coding tools for infrastructure and pipeline work
Requirements
What you’ll need- 5+ years in platform engineering, SRE, MLOps, or infrastructure
- Hands-on experience deploying and operating ML or AI workloads in production
- Strong SRE/DevOps foundation
- Deep IaC expertise
- Strong GitOps background
- Deep Kubernetes knowledge
- Strong AWS background
- Hands-on experience building and operating CI/CD pipelines
- Automation-first thinking at a senior level
- Active user of agentic coding tools
- Strong communicator
Benefits
Comp & perks- Paid time off
- Flexible work arrangements
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ML deployment lifecycleML pipelinesinfrastructure-as-codeGitOpsKubernetesAWSCI/CD pipelinesagentic coding toolsML reliabilityML observability
Soft Skills
strong communicatorautomation-first thinking