Machine Learning Developer
Tasks
- Build AI powered Python applications
- Build LLM monitoring and observability
- Build retrieval-augmented generation pipelines
- Create GenAI templates and reusable tooling
- Create LLM evaluation frameworks
- Define SLOs for ML workloads
- Deploy applications to Kubernetes using GitOps
- Develop agent based application patterns
- Develop internal AI platform tooling
- Implement AI ML pipeline orchestration
- Implement LLMOps model gateway integration
- Implement embeddings monitoring
- Implement logging and alerting for ML pipelines
- Implement service mesh traffic management
- Improve production reliability for model retraining loops
- Integrate enterprise security tooling into workflows
- Manage prompts and safety controls
- Monitor model drift and quality
- Optimize LLM cost and performance
- Support incident response and root cause analysis
- Troubleshoot AI ML and GenAI pipelines
Perks/Benefits
Skills/Tech-stack
AI Pipelines | Agent Frameworks | Airflow | ArgoCD | Arize | Best practices | BigQuery | Composer | Dataflow | Dataflow pipelines | Dataproc | Dataproc jobs | Docker | Error Budgets | GKE | Gemini Enterprise | GitHub Actions | GitOps | Istio | Istio gateways | Istio traffic management | Kubernetes | LLMOps | Langchain | Langgraph | Langsmith | Litellm | MLOps | Model deployments | Model gateways | New Relic | NexusIQ | PagerDuty | Posture Management | Prompt versioning | Python | RAG | RBAC | Retrieval-Augmented Generation | SRE Best Practices | Security Posture | Security posture management | Service Mesh | Splunk | StackRox | Traffic Management | Vertex AI | Vertex AI model deployments | Vertex AI pipelines | Wiz
Education
Associate Degree | Bachelor of Engineering | Bachelor of Science
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