Need:: MLOps Architect for Woodland Hills, CA

[Ishita]

Job Title: MLOps Architect – Databricks Implementation
Location: Woodland Hills, CA – 100% Onsite
Duration: 12+ Months

Position Overview

We are seeking an experienced MLOps Architect with strong expertise in Databricks and AWS based ML/AI infrastructure. The ideal candidate will lead the design and implementation of scalable machine learning platforms in a multi tenant SaaS environment. This role requires deep experience across MLOps architecture, ML pipeline orchestration, cloud infrastructure, and enterprise data platforms. The architect will work closely with data scientists, data engineers, DevOps teams, and enterprise architects to build scalable, secure, and production ready ML platforms.

Key Responsibilities

1. ML Platform Architecture
   Architect and implement scalable AWS based ML and AI cloud infrastructure supporting multi tenant SaaS environments.

2. ML Lifecycle Management
   Collaborate with data scientists, data engineers, and IT teams to define best practices for machine learning model development, deployment, monitoring, and lifecycle management.

3. MLOps Platform Strategy
   Evaluate and recommend ML Ops platforms, tools, and cloud technologies while ensuring alignment with enterprise architecture standards.

4. ML Pipeline Integration
   Oversee the integration of ML pipelines with enterprise data platforms and application architectures. Experience integrating with enterprise systems such as Guidewire is highly desirable.

5. Kubernetes and Workflow Orchestration
   Oversee ML and AI Kubernetes cluster management and guide teams on workflow orchestration frameworks such as Argo, Kubeflow, and Apache Airflow.

6. Infrastructure Automation
   Leverage tools such as Argo CD to automate infrastructure provisioning, deployment pipelines, and operational management of ML platforms.

7. Platform Governance and Best Practices
   Define governance standards, platform best practices, and architectural guidelines for ML platform development and deployment.

8. Technical Leadership
   Provide technical leadership and mentorship to engineering and data science teams on MLOps architecture, tooling, and enterprise ML platform best practices.

Data and Analytics Technology Experience

1. 5+ years of experience defining AI and ML strategies and technology roadmaps.

2. 4+ years of experience with MLOps platforms such as AWS SageMaker, Google Vertex AI, or Databricks.

3. 3+ years of experience implementing ML and data pipeline orchestration using tools such as Kubeflow or Apache Airflow.

4. 2+ years of experience working with ML feature store technologies such as Tecton, Databricks Feature Store, or FeatureForm.

5. 3+ years of experience with DevOps automation tools such as Argo CD or Argo Workflows and container orchestration platforms including Kubernetes or ROSA.

6. 3+ years of experience integrating enterprise applications such as Guidewire or Salesforce.

7. 4+ years of experience working with enterprise data platforms such as Snowflake, Amazon Redshift, or Google BigQuery.

8. 2+ years of experience working with Generative AI tools and large language models such as OpenAI, Gemini, or similar frameworks.

9. 1+ year of experience working with Agentic AI frameworks such as LangGraph, Autogen, or Google ADK.

10. 3+ years of experience working with API orchestration tools such as MuleSoft or Google Cloud API platforms.

Architecture Experience

1. 3+ years of experience implementing Data Mesh architecture and designing data products.

2. 3+ years of experience working with Event Driven Architecture frameworks.

3. 4+ years of experience designing scalable AWS based ML and AI cloud infrastructure for enterprise environments.

4. 3+ years of experience defining enterprise data architecture guidelines and governance standards.

5. 3+ years of experience designing secure distributed systems and implementing enterprise security architectures.

6. 4+ years of experience designing scalable and decoupled enterprise systems.

7. 5+ years of experience developing enterprise technology strategies and architecture roadmaps.

8. 3+ years of experience driving architectural decisions using data driven insights.

Domain Experience (Preferred)

1. 4+ years of experience working in the insurance domain including policy management, claims processing, or insurance services operations.

2. 2+ years of experience with legal and regulatory compliance requirements within the insurance industry.

3. 3+ years of experience developing domain specific data products.

4. 2+ years of experience implementing AI driven business process automation.

Experience Required

1. Minimum 10+ years of experience in machine learning engineering, data platform architecture, or MLOps architecture roles.

2. Proven experience designing and implementing enterprise scale ML platforms using Databricks and cloud based infrastructure.

---
Thanks & Regards
Ishita Bali
Novia Infotech LLC
4421 Avenida Ln, McKinney, TX 75070
Email: ishi...@noviainfotech.com