Zefr

Zefr

Senior Software Engineer

Marina del Rey, CA · Senior

Sponsorship not specifiedDetected 92 days ago
PythonDistributed SystemsData StructuresAlgorithmsCode ReviewGitPostgreSQLElasticsearchSnowflakeAWSGCPAzureCloud PlatformsDockerKubernetesTerraformGitHub ActionsDevOpsAPI DevelopmentKafkaMachine LearningPandasLLMsDesign Systems

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odds of building a lasting career here

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Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • WHAT WE DO: Zefr is the leader in AI-powered content classifications for brands and advertisers.
  • Our products safeguard media and AI investments, while maximizing performance and efficacy on those channels.
  • Headquartered in Los Angeles with global offices across New York, Chicago, London, Toronto, Singapore, and more, Zefr is redefining what trust and transparency means for social media in the age of AI.

Responsibilities

  • Success in this position looks like a self-starter who takes ambiguous problems from design through production, operates what they build, and raises the engineering bar for the team through strong collaboration and clear communication.
  • Own the design and implementation of microservices, and run and operate them in Kubernetes and other cloud-scalable, highly available environments.
  • Collaborate with product, ML, and infrastructure teams to translate requirements into robust technical designs.
  • Contribute to architectural decisions, design reviews, and engineering standards across the platform.
  • Deep hands-on experience designing, building, running, and operating microservices in Kubernetes and cloud environments (GCP, AWS, or Azure)
  • Strong foundation in distributed systems, API design, data structures, algorithms, and software design
  • We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better.

Requirements

  • Bachelor's or Master's degree in Computer Science or related field with 5+ years of professional software engineering experience
  • Proficiency using AI for coding and research as a daily productivity multiplier (e.g., Claude Code, Copilot, Cursor)

Nice to have

  • Big plus: proficiency with LLMs, MCP (Model Context Protocol), agent-gateway, and agentic infrastructure

Compensation

  • The anticipated salary for this position is between $180K and $200K.
  • Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training.
  • If your compensation expectations fall outside of this range, it may still be worth having a conversation.

Benefits

  • Medical, dental, and vision insurance with FSA options
  • Company-paid life insurance
  • Paid parental leave
  • Summer Fridays (we leave early)
  • Design systems for scale, reliability, and high availability, and take accountability for the operational health of owned services, including observability, alerting, and incident response.

Company info

  • Zefr is the leader in AI-powered content classifications for brands and advertisers.
  • Zefr's platform is purpose built for multi-modal content understanding on open platforms like YouTube, TikTok, Meta and Snap, with pre-bid activation and verification solutions.
  • We are hiring a Senior Software Engineer to own the design, implementation, and operation of microservices running in Kubernetes and other cloud-scalable, highly available environments.
  • In this role you will build and run the production systems that power Zefr's platform at scale, and you will use AI fluently - for coding, research, and problem-solving - as a core part of how you work.
  • Use AI tools for coding and research as a daily part of the engineering workflow, and help the team adopt effective AI-assisted development practices.

Equal opportunity

  • Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace.

This listing is sourced directly from Zefr's careers page and normalized into a canonical job model.