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Remote Ai Data Engineer Jobs in San Ramon, CA (NOW HIRING)

Lancesoft

Data Engineer (Remote)

San Francisco, CA · On-site +1

$40 - $41/hr

Lead Data Engineer -Data & AI, Supply Chain Fully Remote Rate: $40/hour About the Role Tech is seeking an experienced Lead Data Engineer to join the Supply Chain Data & AI Organization. This role ...

Allocate

Sr. Data Engineer

Palo Alto, CA · Remote

$134K - $161K/yr

This is a fully remote position where you will work alongside our backend team (C#/.NET) and ... Enable AI/ML Capabilities: Work closely with our data science and engineering team to provision the ...

10a Labs

Data Engineer, Web Scraping

San Francisco, CA · Remote

$105K - $125K/yr

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs ... Fully remote, U.S.-based * Health Benefits: Comprehensive health, dental, and vision coverage

Lever Demo 2

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Lever Demo 2

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Design and build data foundations that enable AI/ML capabilities - feature stores, embedding pipelines, vector search indexes, and model training datasets * Align data engineering solutions with ...

Robert Half

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Design and build data foundations that enable AI/ML capabilities - feature stores, embedding pipelines, vector search indexes, and model training datasets * Align data engineering solutions with ...

The Rockridge Group

Data Engineer

Emeryville, CA · Remote

$132K - $159K/yr

TITLE: DATA ENGINEER LOCATION: 100% remote Skillsets/experience: * Engineer background * Google Applications/Analytics experience required * Google Search console experience required * Google Tag ...

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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 ... Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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All JobsAi Data Engineer JobsRemote Ai Data Engineer JobsRemote Ai Data Engineer Jobs in San Ramon, CA

Remote Ai Data Engineer information

See San Ramon, CA salary details

$49.7K

$145K

$198.4K

How much do remote ai data engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote ai data engineer in San Ramon, CA is $144,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $153,700.00 per year, depending on experience, location, and employer.

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

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

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.
What are popular job titles related to Remote Ai Data Engineer jobs in San Ramon, CA? For Remote Ai Data Engineer jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Remote Ai Data Engineer jobs in San Ramon, CA look for? The top searched job categories for Remote Ai Data Engineer jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Remote Ai Data Engineer jobs? Cities near San Ramon, CA with the most Remote Ai Data Engineer job openings:
Remote Ai Data Engineer jobs near you

AI Data Engineer - Scientific Data Platforms (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$35 - $38/hr

Full-time

Re-posted 23 days ago

Job description

Pay Rate Low: 35 | Pay Rate High: 40
Our client is a leading global biotechnology and pharmaceutical organization driven by a mission to innovate, continuously advance science, and ensure everyone has access to the healthcare they need.
Title: AI Data Engineer - Scientific Data Platforms
Location: Remote, Must work PST
Pay rate: $35-38/hr (Depends on experience level)
Schedule: Full-time (40 hours/week)
Duration: 1-year contract, (Plus benefits)
Position Overview
This role addresses a critical need in scaling our AI models for drug discovery by building largely automated, scalable, agent-driven data ingestion and curation pipelines for genomics data. This includes metadata inference, constructing performant query architectures, and transforming high-dimensional datasets (e.g., single-cell omics, clinical trials) into AI-ready training formats.
Key Responsibilities
  • Build an agentic data ingestion pipeline and move beyond bespoke steps toward agents that teams can reliably use as a shared, deployed service.
  • Triage and prioritize incoming requests to ingest specific datasets. Clean and organize data, building the first-pass cleaning and organization steps into the agentic flow.
  • Validate cross-modal linkage. Add automated checks that catch when ingested data does not connect correctly and flag low-quality or mismatched records.
  • Version every dataset, retaining and making prior versions addressable. Preserve raw data and provenance, ensuring agent workflows log validation and transformation steps so lineage is fully traceable.
  • Partner with AI, software engineering, and computational biology groups to co-define data standards and conventions.

Qualifications & Requirements
  • Demonstrated experience building multi-agent workflows or LLM workflows using tools/frameworks such as LangGraph or LlamaIndex, including tool/function calling and asynchronous task execution.
  • Strong Python skills for data manipulation, working with APIs and databases, and handling heterogeneous data formats.
  • Familiarity with dataset versioning approaches (e.g., DVC, lakeFS, or equivalent).
  • Comfortable with or showing a strong willingness to learn common omics data formats like AnnData, H5AD, and TileDB.
  • No deep bioinformatics expertise required; just a basic conceptual understanding of different modalities (e.g., RNA-seq vs. scRNA-seq vs. WES; genomics vs. transcriptomics vs. proteomics vs. metabolomics).
  • Comfortable writing unit and functional tests to ensure data processing workflows are reliable and reproducible.
  • Degree in a technical field or equivalent practical experience.
  • Must be Authorized to work in the United States without Sponsorship.
Nice to Have
  • Experience deploying agent workflows as a shared service (e.g., FastAPI or MCP endpoints).
  • Exposure to cloud platforms (AWS, GCP) and containerization (Docker).
  • Familiarity with scientific workflow managers such as Nextflow or Snakemake.

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