Full-Time

Senior Backend Infrastructure Engineer

Giga AI

Giga AI

51-200 employees

Dataset management and GPT-4 model fine-tuning

Compensation Overview

$200k - $280k/yr

+ Wellness stipend $150/month

San Francisco, CA, USA

In Person

Category
DevOps & Infrastructure (2)
,
Required Skills
Kubernetes
Airflow
Docker
Terraform
Observability
Requirements
  • Have 4+ years of experience in infrastructure, platform, or backend engineering roles
  • Have built systems that other engineers depend on, and understand the responsibility that comes with that
  • Care deeply about reliability, but also know when "good enough" is the right call
  • Are comfortable across the stack, from application code to cloud infrastructure
  • Can debug production issues under pressure and build systems that prevent them from recurring
  • Think about developer experience as a product—you want the tools you build to be a pleasure to use
  • Are excited about the infrastructure challenges of running AI agents at scale
Responsibilities
  • Build and own controlled deployments with staged rollout systems, traffic scaling, scheduling, and pass rate thresholds to safeguard production
  • Create instrumentation, logging, and monitoring infrastructure for observability
  • Build pipelines and storage systems for training data, analytics, and agent memory
  • Develop internal developer tooling, such as CLIs, testing frameworks, and automation to reduce friction for the engineering team
  • Own critical systems end-to-end and make decisions affecting reliability and velocity of the entire engineering team

GigaML helps developers, data scientists, and businesses manage and improve AI models, especially those based on OpenAI’s GPT-4. Its platform lets users create and organize datasets from logs, manage these datasets, and apply various fine-tuning methods to tailor models to specific tasks or industries. The product works by providing an API-backed workflow: sign up, generate an API key, and integrate GigaML’s library into Python or NodeJS projects to upload data, select tags or models, and run fine-tuning operations that adjust a model’s behavior. GigaML differentiates itself through structured dataset management, flexible fine-tuning options, and a usage-based pricing model that scales from startups to large enterprises, enabling clients to pay for data processed and tuning effort. The company aims to help organizations leverage advanced AI more effectively by making it easier to manage data, fine-tune models, and deploy capable AI solutions at scale.

Company Size

51-200

Company Stage

Series A

Total Funding

$64.7M

Headquarters

San Francisco, California

Founded

2023

Simplify Jobs

Simplify's Take

What believers are saying

  • Raised $61M Series A from Redpoint Ventures on November 5, 2025, fueling growth.
  • Partners with DoorDash to automate millions of support calls rapidly.
  • Y Combinator praises Giga as top AI firm from India since 2023 founding.

What critics are saying

  • Full Truck Alliance majority stake since July 9, 2025, triggers CFIUS blocks.
  • Ex-employee lawsuit over revenue fraud erodes trust by mid-2026.
  • OpenAI fine-tuning API since 2024 eliminates third-party demand immediately.

What makes Giga AI unique

  • Giga deploys voice AI agents with sub-second responses for complex enterprise support.
  • Real-time orchestration handles listening, reasoning, and actions simultaneously.
  • Achieves over 90% resolution accuracy in production for DoorDash and finance.

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Benefits

Catered lunch daily

Dinner stipend

$150/month wellness benefit (gym, fitness classes, mental health)

401(k) plan

Paid parental leave (12 weeks maternal, 6 weeks paternal)

Commuter benefits

Medical, dental, and vision coverage

Growth & Insights and Company News

Headcount

6 month growth

18%

1 year growth

-7%

2 year growth

-13%
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