Job ID: JOB_ID_2880
Job Overview:
We are seeking a highly skilled and experienced MLOps Architect with Databricks expertise to join our team. The ideal candidate will be responsible for architecting and implementing scalable AWS ML/AI cloud infrastructure within a multi-tenant SaaS environment. This role requires close collaboration with data scientists, data engineers, and IT teams to define requirements and best practices for the entire ML lifecycle, from development to deployment and monitoring.
Key Responsibilities:
- Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment.
- Collaborate with data scientists, data engineers, and IT teams to define requirements and best practices for ML model development, deployment, and monitoring.
- Evaluate and recommend tools, platforms, and cloud technologies for ML Ops, ensuring alignment with enterprise architecture standards.
- Oversee the integration of ML pipelines with existing enterprise data and application architectures. Familiarity with Guidewire integrations is highly desirable.
- Oversee ML/AI related Kubernetes cluster management and provide guidance on alternative ML/AI workflow orchestration options such as Argo vs Kubeflow, and ML/AI data pipeline creation, management, and governance with tools like Airflow.
- Employ tools like Argo CD to automate infrastructure deployment and management.
- Mentor and guide technical teams on ML Ops architecture, tooling, and best practices.
Required Technical Experience:
- 5+ years: AI/ML Strategy & Roadmap Development.
- 4+ years: ML Ops Tools (e.g., AWS Sagemaker, GCP Vertex AI, Databricks).
- 3+ years: ML & Data Pipeline Orchestration (e.g., Kubeflow, Apache Airflow).
- 2+ years: ML Feature Store Tools (e.g., Tecton, Databricks, FeatureForm).
- 3+ years: DevOps (e.g., Argo CD / Argo Workflows), Containerization (Kubernetes, ROSA).
- 3+ years: Enterprise Application Integration (e.g., Guidewire, Salesforce).
- 4+ years: Data Platforms (e.g., Snowflake, RedShift, BigQuery).
- 2+ years: GenAI Tools / LLMs (e.g., OpenAI, Gemini, etc.).
- 1+ year: Agentic AI Frameworks (e.g., LangGraph, Autogen, Google ADK).
- 3+ years: API Orchestration (e.g., Mulesoft, Google Cloud API).
Required Architecture Experience:
- 3+ years: Data Mesh Architecture & Data Product Design.
- 3+ years: Event-Driven Architecture (EDA).
- 4+ years: Scalable AWS ML/AI Cloud Infrastructure (Multi-tenant SaaS).
- 3+ years: Data Architecture Guidelines Development.
- 3+ years: Security in Distributed Systems.
- 4+ years: Designing Scalable, Decoupled Systems.
- 5+ years: Strategy & Roadmap Creation.
- 3+ years: Influencing with Data-Driven Insights.
Required Domain Experience:
- 4+ years: Functional Knowledge of Insurance Domains (Policy, Claims, Services Ops) – Preferred.
- 2+ years: Legal & Compliance Regulations in Insurance – Preferred.
- 3+ years: Data Product Development for Functional Domains.
- 2+ years: AI-Driven Business Process Automation.
Additional Information:
This is a contract position requiring the candidate to work onsite in Woodland Hills, CA. Local candidates are preferred. The role involves working with cutting-edge technologies in AI/ML and cloud infrastructure.
Special Requirements
Need Local candidates. Onsite work required.
Compensation & Location
Salary: $120 – $160 per year (Estimated)
Location: Woodland Hills, CA
Recruiter / Company – Contact Information
Email: tushar.b@metrixit.co
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