Technology

Sr DevOps Engineer

Relevance Lab Inc.Los Angeles, CA🇺🇸United States

Why this role stands out

This Sr. DevOps Engineer role offers an exciting opportunity to shape the future of Generative AI applications, providing significant impact and advanced technical challenges. You'll thrive here if you have a strong background in DevOps and a passion for scaling innovative AI platforms, driving the company's strategic development. Apply now to be at the forefront of AI advancement!

Quick overview

SeniorityMid Senior

Work modeOn Site

LocationLos Angeles, CA, United States

DockerShellGitMLOpsMLflowAnsibleGitHub ActionsGoogle CloudPythonTerraformGenerative AIAzureKubernetesCI/CD

Job description

DevOps Engineer, Generative AI Applications

LOCAL TO LA, PST HRS

Job Summary:

Lead comprehensive applications/web development for highly complex projects; typically work as part of a team to implement complex business solutions. Deliver strategic and expert coding; focus on overarching development strategy for a large, complex, multi-faceted application. May manage a number of projects simultaneously.

You will also help us build and scale our GenAI application platform. This platform will be the hub within the organization where GenAI application developers can share their data and code. As custodians of this platform, we intend to use the best practices in the field along with existing repositories to expedite the path from prototype for GenAI applications and unlock economies of scale. You will be highly influential in advancing our GenAI applications and guide teams towards impactful and ethical AI. We seek an expert who is eager to grow and disseminate GenAI model expertise across the organization.

Job-Specific Responsibilities:

Minimum of 8 to 10 years post-secondary education or relevant work experience
Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired
Minimum of five years DevOps experience with at least a year of ML Ops and Software Engineering Development background
Cloud Platforms: Proficiency in cloud services - Nice to have - Google Cloud Platform (Google Cloud Platform), or Microsoft Azure.
Containerization & Orchestration: Expertise with Docker and Kubernetes for managing application environments.
Infrastructure as Code (IaC): Experience with tools like Terraform or Ansible for automating infrastructure provisioning.
Programming: Strong scripting skills, typically in Python or Go, for automation and building operational tools.
MLOps Tools: Familiarity with MLOps platforms and tools (e.g., MLflow, Kubeflow, Data Version Control (DVC)) is often a plus.
SRE Mindset: A focus on site reliability engineering principles to ensure robust production systems.
Tech Skills: Terraform, GitHub actions, Quadrant, Vector Database, CI/CD, Python, Shell Scripting.
Strong Communication Skills, Good Team Player, ability to wear multiple hats, fast learner, problem solving and go getter attitude.