- Location
- Los Angeles, CA
- Workplace
- Onsite
- Type
- Full-time
- Department
- Technology and Operations
- Seniority
- Director
- Experience
- 7+ years
- Education
- Master
- Source
- Lever
Description
ABOUT CIM GROUP:
CIM is a community-focused real estate and infrastructure owner, operator, lender, and developer. Our team of experts works together to identify and create value in real assets, benefiting the communities in which we invest. Back in 1994, our three founders focused on projects in Southern California neighborhoods. Today, we are a diverse team of 900+ employees with projects across the Americas. Our projects have delivered jobs; created comfortable places to live, work, and relax; and provided necessary and sustainable infrastructure. Our focus on enhancing communities is unwavering, and we strive to make an even greater impact in the years to come. Join us and make an impact today!
POSITION PURPOSE:
The Senior ML Ops Engineer leads the design and maintenance of scalable, secure infrastructure for ML model deployment, lifecycle management, and Generative AI enablement. This role is responsible for building and operating the firm's ML Ops platform on Databricks, with a strategic focus on productionizing GenAI/LLM solutions including Retrieval-Augmented Generation (RAG) systems and vector database implementations.
The Senior ML Ops Engineer ensures models transition from development to production while meeting regulatory and compliance standards. This role collaborates closely with Data Science, Platform Engineering, Information Architecture, and business vertical teams (Fund Accounting, Investor Relations, Investments) to accelerate ML-driven insights, enhance model accuracy, and govern the ML/AI ecosystem.
Beyond technical execution, the role defines ML Ops strategy and architecture, addressing the "last mile" challenge of AI value realization by automating and scaling ML models and GenAI applications as tangible business assets. This role serves as the key pillar that enhances efficiency, boosts model accuracy, accelerates time-to-market for AI solutions, and ensures the scalability and robust governance of machine learning and generative AI initiatives.
Skills
PythonAzureGCPDockerKubernetesJenkinsCI/CDSQLMachine LearningTensorFlowPyTorchScikit-learnAirflowDatabricksData ScienceETLGitHubGitLabDevOpsCompliance
