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Remote Data Infrastructure Jobs in California (NOW HIRING)

talentpluto

Research Engineer

San Francisco, CA · On-site +1

$140K - $250K/yr

Remote Industry: AI training data infrastructure Compensation: $140K-$250K base, plus equity About the Company Our partner is a YC-backed company building a new kind of marketplace in the AI training ...

Pinterest

Staff Technical Program Manager

San Francisco, CA · On-site +1

$152K - $196K/yr

Own Presto query optimization and support for our analytics agent, keeping the data infrastructure ... Visit our PinFlex page to learn more about our working model. #LI-REMOTE #LI-DM57 At Pinterest we ...

ServiceNow

Director, Data Strategy & Services

Santa Clara, CA · On-site +1

$173K - $238K/yr

  • Medical

  • Retirement

... data infrastructure that powers personalization, attribution, and AI-driven revenue decisions ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

ServiceNow

Director, Data Strategy & Services

Santa Clara, CA · On-site +1

$173K - $238K/yr

  • Medical

  • Retirement

... data infrastructure that powers personalization, attribution, and AI-driven revenue decisions ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

ServiceNow

Director, Data Strategy & Services

Santa Clara, CA · On-site +1

$173K - $238K/yr

  • Medical

  • Retirement

... data infrastructure that powers personalization, attribution, and AI-driven revenue decisions ... Work personas (flexible, remote, or required in office) are categories that are assigned to ...

Cystems Logic Inc

Data Lead - REMOTE

Los Angeles, CA · On-site +1

Data Lead Duration : Longterm Contract Location: Remote We have below longterm job opening. If you ... Knowledge of CI/CD, Infrastructure as Code (IaC), and DevOps practices. Experience with ...

New

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

... the infrastructure and delivery of our core consumer and enterprise data offerings as well as ... This is a remote position. Duties * Support production systems and help triage issues during live ...

Corvus Robotics

Sr. ML Ops Engineer

Mountain View, CA · On-site +1

$123K - $169K/yr

... remote role with periodic trips to HQ in Mountain View, CA. Must Haves * 2-3 years shipping real production ML infrastructure for big datasets, not just scripts * Experience building distributed data ...

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... computing infrastructures (AWS) * Experience with web scraping and cleaning unstructured data

Tetra Tech

Infrastructure Specialist (San Diego, CA)

San Diego, CA · Remote

$130K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... data centers, industrial facilities, utility-related systems, and remote connectivity. Primary Responsibilities: * Lead the architecture, design, implementation, and ongoing support of infrastructure ...

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Remote Data Infrastructure information

What are the key skills and qualifications needed to thrive as a remote data infrastructure engineer?

To excel as a Remote Data Infrastructure Engineer, you need a strong background in computer science, data architecture, and experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with tools like Terraform, Kubernetes, and data pipeline technologies, as well as relevant certifications (e.g., AWS Certified Solutions Architect), is typically required. Strong problem-solving abilities, clear communication, and self-motivation are essential soft skills for remote collaboration and troubleshooting. These competencies ensure reliable, scalable data systems and effective teamwork across distributed environments.

What are some common challenges faced by professionals working in remote data infrastructure roles?

Professionals in remote data infrastructure roles often encounter challenges such as ensuring seamless communication across distributed teams, maintaining high availability and performance of data systems, and managing security risks associated with remote access. Coordinating with colleagues across different time zones can require flexibility in scheduling and proactive communication. Additionally, remote data infrastructure engineers must stay up-to-date with evolving cloud technologies and best practices to effectively support scalable, reliable, and secure data architectures.

What is remote data infrastructure?

Remote data infrastructure refers to the systems, tools, and processes that enable organizations to collect, store, manage, and analyze data from remote locations, often via cloud-based platforms. This infrastructure allows teams to access and work with data securely from anywhere, supporting distributed work environments and scalable data solutions. It typically involves cloud storage, data pipelines, databases, and security protocols tailored for remote accessibility. Remote data infrastructure is essential for businesses that operate in multiple locations or have remote teams.
What are the most commonly searched types of Data Infrastructure jobs in California? The most popular types of Data Infrastructure jobs in California are:
What are popular job titles related to Remote Data Infrastructure jobs in California? For Remote Data Infrastructure jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Data Infrastructure jobs in California look for? The top searched job categories for Remote Data Infrastructure jobs in California are:
What cities in California are hiring for Remote Data Infrastructure jobs? Cities in California with the most Remote Data Infrastructure job openings:
Remote Data Infrastructure jobs near you
Infographic showing various Remote Data Infrastructure job openings in California as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 8% Part Time, and 7% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Research Engineer

talentpluto

San Francisco, CA • On-site, Remote

$140K - $250K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Location: Remote (United States)
Work Model: Remote
Industry: AI training data infrastructure
Compensation: $140K-$250K base, plus equity
About the Company
Our partner is a YC-backed company building a new kind of marketplace in the AI training data space. Rather than operating as a labor marketplace, they provide infrastructure that lets data producers transform their existing data into formats AI labs want and sell it directly to those labs. This democratized model unlocks far more high-value data sources, and the team is growing quickly to keep up with demand.
The Opportunity
This is the company's top hiring priority and a genuinely hard research problem. Because data flows through a decentralized marketplace, ensuring quality at scale is the single biggest bottleneck to growth. As a Research Engineer, you will build the automated systems that verify and assure data quality so that suppliers consistently deliver excellent data to buyers.
You will start by digging into the data manually to understand failure modes, then design systems to automate quality checks at scale, combining rule-based approaches with AI for fuzzier cases and human-in-the-loop review where it makes sense. This is fundamentally a research role focused on building automated systems, not manual QA.
Responsibilities
  • Identify data quality issues including inconsistencies, formatting problems, and ingestion challenges
  • Perform initial manual data quality review to deeply understand failure modes
  • Build systems to automate quality checks at scale using rule-based and AI-driven approaches
  • Design hybrid systems that balance automation with human-in-the-loop review where appropriate
  • Continuously improve verification methods as the data landscape and AI tooling evolve
Requirements
  • Deeply technical, with a strong learning slope and the ability to ramp quickly in a fast-moving field
  • Background in AI/ML engineering, or software engineering at an AI-focused company with visible data ingestion and processing experience
  • Ability to reason about likely data quality problems from first principles
  • Comfortable owning ambiguous, open-ended problems end to end
  • Comfortable working in person, full-time, in a San Francisco office
  • Bonus: experience working with noisy or unstructured data, or judgment on when to use automation versus human-in-the-loop review

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