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Remote Dimensional Engineer Jobs in California (NOW HIRING)

YO AI Labs

SolidWorks Expert - Remote

Los Angeles, CA · Remote

$40 - $130/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, tolerance application, manufacturability, and ...

YO AI Labs

SolidWorks Expert - Remote

San Francisco, CA · Remote

$40 - $130/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, tolerance application, manufacturability, and ...

YO AI Labs

SolidWorks Expert - Remote

San Jose, CA · Remote

$40 - $130/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, tolerance application, manufacturability, and ...

YO AI Labs

SolidWorks Expert - Remote

Palo Alto, CA · Remote

$40 - $130/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, tolerance application, manufacturability, and ...

YO AI Labs

Autodesk Inventor Expert - Remote

Palo Alto, CA · On-site +1

$30 - $120/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, GD&T compliance, manufacturability, and ...

YO AI Labs

Autodesk Inventor Expert - Remote

San Jose, CA · On-site +1

$30 - $120/hr

No prior AI experience is required--your engineering and CAD expertise are what matter most. Key ... Review and audit CAD models for dimensional accuracy, GD&T compliance, manufacturability, and ...

Selector Software, Inc.

Solutions Engineer

Santa Clara, CA · On-site +1

$140K - $170K/yr

By adopting an AI/ML-based analytics approach, the platform provides actionable multi-dimensional ... Remote and hybrid arrangements are not available for this position. Responsibilities * Serve as a ...

6sense

Sr. Software Engineer

San Francisco, CA · Remote

$179K - $263K/yr

... dimensional analysis) * Design and implement reliable, scalable, robust and extensible big data ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site +1

$144K - $194K/yr

The hybrid-remote Principal Software Development Engineer leads the design, development, and ... dimensional search requirements. * Troubleshoot Complex AI Issues: Resolve deep technical ...

NextDeavor Inc.

Principal Data Architect

Irvine, CA · Remote

$126K - $214K/yr

Principal Data Architect Full-time Remote Exclusive confidential search -- details shared with ... coach engineers on dimensional modeling and Data Vault approaches. * Identify tooling and ...

Block

Senior Data Engineer, Risk

Bodega Bay, CA · On-site +1

$125K - $170K/yr

Today, Cash App has thousands of employees working globally across office and remote locations ... Experience in schema design and dimensional data modeling * Experience with setting up data quality ...

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Remote Dimensional Engineer information

What is a remote dimensional engineer?

A Remote Dimensional Engineer is a professional who specializes in ensuring that components and assemblies meet precise dimensional specifications, often within manufacturing or engineering environments. Working remotely, they use advanced software and digital tools to analyze blueprints, 3D models, and data from measurement systems to detect and solve dimensional issues. Their work is critical in maintaining quality standards, reducing errors, and supporting efficient production processes. Remote Dimensional Engineers often collaborate with on-site teams and may provide guidance on measurement techniques or quality control improvements.

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

To thrive as a Remote Dimensional Engineer, you need a solid background in dimensional analysis, metrology, and engineering principles, often backed by a degree in mechanical or manufacturing engineering. Proficiency with CAD software, coordinate measuring machines (CMM), and dimensional data analysis tools, as well as certifications like GD&T, is typically required. Attention to detail, effective communication, and problem-solving skills are crucial for collaborating remotely and ensuring accurate measurements. These competencies are vital for maintaining product quality and specification compliance in distributed or remote manufacturing environments.

What are the common challenges faced by remote dimensional engineers, and how can they be managed effectively?

Remote Dimensional Engineers often encounter challenges related to communication and data validation, as they typically collaborate with cross-functional teams and rely on digital tools to assess dimensional accuracy. Managing time zones, ensuring clear documentation, and maintaining data security are important aspects of the remote work structure. Utilizing robust 3D modeling software, establishing regular virtual meetings, and leveraging cloud-based collaboration platforms can help address these challenges and foster effective teamwork.

What is the difference between Remote Dimensional Engineer vs Remote Mechanical Engineer?

AspectRemote Dimensional EngineerRemote Mechanical Engineer
Required CredentialsBachelor's in Engineering, CAD proficiency, dimensional analysis skillsBachelor's in Mechanical Engineering, CAD proficiency, design experience
Work EnvironmentDesign labs, CAD software, remote collaboration toolsManufacturing sites, design offices, remote work possible
Industry UsageProduct development, quality control, precision measurementProduct design, systems engineering, manufacturing processes

The main difference between a Remote Dimensional Engineer and a Remote Mechanical Engineer lies in their focus areas. Dimensional Engineers specialize in precision measurement and quality control of components, often working with CAD and measurement tools. Mechanical Engineers have a broader scope, including designing, analyzing, and testing mechanical systems. Both roles may work remotely, but their core responsibilities and industry applications differ slightly.

What are the most commonly searched types of Dimensional Engineer jobs in California?

The most popular types of Dimensional Engineer jobs in California are:

What are popular job titles related to Remote Dimensional Engineer jobs in California?

For Remote Dimensional Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Dimensional Engineer jobs in California look for?

The top searched job categories for Remote Dimensional Engineer jobs in California are:

What cities in California are hiring for Remote Dimensional Engineer jobs?

Cities in California with the most Remote Dimensional Engineer job openings:

Remote Dimensional Engineer jobs near you
Infographic showing various Remote Dimensional Engineer job openings in California as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% Remote job distribution.

AI Data Engineer - Scientific Data Platforms (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$35 - $38/hr

Full-time

Re-posted 3 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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