MLOps Engineer
Automating the ML model lifecycle: from training to production monitoring
MLOps Engineer is a role in the ML & AI Engineering family. It has 56 skills across 5 levels (from Junior to Principal). 123 skills are mandatory. Key domains: Programming Fundamentals, Backend Development, Database Management.
Technology Stack
Focus by Level
Setting up ML pipelines. Working with MLflow/DVC. Containerizing models. Monitoring inference. Automating routine tasks.
Designing CI/CD for ML. Setting up feature store. Automating training and deployment. Drift monitoring. GPU cluster management.
MLOps platform architecture. Inference optimization (Triton, ONNX). Real-time serving. GPU autoscaling. Cost optimization.
MLOps platform strategy. ML lifecycle standards. Coordination with ML and backend teams. Vendor evaluation.
Enterprise MLOps architecture. Multi-cloud ML infrastructure. LLM deployment strategy. Industry best practices.
Skill Matrix
56 skills × 5 levels. Click on a cell for details.
AI-Assisted Development
4 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| GitHub Copilot | A | W | A | E | E |
| Cursor IDE | A | W | A | E | E |
| ChatGPT / Claude | A | W | A | E | E |
| Prompt Engineering for Code | A | W | A | E | E |
API & Integration
4 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| REST API Design | A | W | A | E | E |
| GraphQL Design | A | W | A | E | E |
| gRPC & Protocol Buffers | A | W | A | E | E |
| API Documentation | A | W | A | E | E |
Architecture & System Design
1 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| System Design Fundamentals | A | W | A | E | E |
Backend Development
5 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Python Web Frameworks | A | W | A | E | E |
| Apache Kafka | A | W | A | E | E |
| Redis | A | W | A | E | E |
| Task Queues | A | W | A | E | E |
| S3 / Object Storage | A | W | A | E | E |
Cloud & Infrastructure
8 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Docker | A | W | A | E | E |
| Container Security Scanning | A | W | A | E | E |
| Kubernetes Core | A | W | A | E | E |
| Kubernetes Advanced | A | W | A | E | E |
| Helm | A | W | A | E | E |
| Terraform | A | W | A | E | E |
| AWS | A | W | A | E | E |
| Network Fundamentals | A | W | A | E | E |
Database Management
3 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| PostgreSQL | A | W | A | E | E |
| Database Indexing | A | W | A | E | E |
| Query Optimization | A | W | A | E | E |
DevOps & CI/CD
3 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| GitHub Actions / GitLab CI | A | W | A | E | E |
| GitLab CI/CD Advanced | A | W | A | E | E |
| ArgoCD | A | W | A | E | E |
Machine Learning & AI
6 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| MLflow | A | W | A | E | E |
| Feature Stores | A | W | A | E | E |
| Model Serving | A | W | A | E | E |
| Experiment Tracking | A | W | A | E | E |
| ML Pipelines | A | W | A | E | E |
| Model Monitoring | A | W | A | E | E |
Observability & Monitoring
5 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Structured Logging | A | W | A | E | E |
| Prometheus & Grafana | A | W | A | E | E |
| Custom Business Metrics | A | W | A | E | E |
| OpenTelemetry | A | W | A | E | E |
| SLI / SLO / SLA | A | W | A | E | E |
Programming Fundamentals
8 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Algorithms & Complexity | A | W | A | E | E |
| Data Structures | A | W | A | E | E |
| OOP & SOLID Principles | A | W | A | E | E |
| Design Patterns | A | W | A | E | E |
| Multithreading | A | W | A | E | E |
| Async Programming | A | W | A | E | E |
| Code Quality & Refactoring | A | W | A | E | E |
| Type Safety & Type Systems | A | W | A | E | E |
Security
3 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| OWASP & Application Security | A | W | A | E | E |
| Secure Coding Practices | A | W | A | E | E |
| JWT / OAuth2 / OIDC | A | W | A | E | E |
Testing & QA
4 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Unit Testing | A | W | A | E | E |
| Integration Testing | A | W | A | E | E |
| E2E Testing | A | W | A | E | E |
| Load Testing | A | W | A | E | E |
Version Control & Collaboration
2 skills| Skills | Jun | Mid | Sen | Lead | Princ |
|---|---|---|---|---|---|
| Git Advanced | A | W | A | E | E |
| Code Review | A | W | A | E | E |
FAQ
What skills are needed for the MLOps Engineer role?
The MLOps Engineer role requires 56 skills, of which 123 are mandatory. Skills are distributed across 5 levels: from Junior to Principal. See full matrix.
How to advance to the next level in the MLOps Engineer role?
Use the Grade Calculator to assess your current level and get personalized recommendations. The system will show which skills need to be developed for the next level.
What tech stack is used in the MLOps Engineer role?
The stack includes 5 technologies at different levels. Python, MLflow, DVC, Docker, Airflow basics, Kubernetes basics, Git, Prometheus basics, Python, Kubeflow/MLflow, Docker/Kubernetes, Airflow, Feature Store (Feast), Seldon/BentoML, Terraform, GitHub Actions, Kubeflow/Vertex AI, Triton Inference Server, ONNX/TensorRT, Kubernetes (GPU scheduling), Ray Serve, Custom operators, Prometheus/Grafana...
How does the community define requirements for the MLOps Engineer role?
Role requirements are shaped by the community through a proposal system. Any member can suggest changes that go through voting and expert review.