ZipRecruiter

Log In

1

Metadata Library Jobs in Michigan (NOW HIRING)

FastTek

Data Engineering Engineer

Dearborn, MI · On-site

$105K - $126K/yr

... metadata conflicts) during the transfer. You will be responsible for consuming Teamcenter APIs ... Familiarity with AI/ML frameworks (e.g., Python-based libraries like Scikit-learn or Pandas, or LLM ...

Corning

... metadata, and lifecycle status are maintained. - Develop and maintain responsible AI templates ... domain-specific guardrail libraries; standardize governance artifacts; define end-user ...

Stefanini Group

GCP Data Engineer

Dearborn, MI

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Stefanini Group

GCP Data Engineer

Dearborn, MI · On-site

$61 - $66/hr

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Stefanini Group

GCP Data Engineer

Dearborn, MI

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Stefanini Group

GCP Data Engineer

Dearborn, MI

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site

$102K - $140K/yr

... curated library of critical driving scenarios. By mining driving logs for long-tail events, we ... metadata integrity. * Data Flywheel Integration: Manage the ingestion of tagged events into the ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

... curated library of critical driving scenarios. By mining driving logs for long-tail events, we ... metadata integrity. * Data Flywheel Integration: Manage the ingestion of tagged events into the ...

previous pagenext page

Showing results 21-40

All JobsMetadata Library JobsMetadata Library Jobs in Michigan

Metadata Library information

What is a metadata librarian?

Metadata librarians are information professionals who manage and organize metadata, which is data that describes other data, for library collections. They create, edit, and maintain metadata records to ensure resources are discoverable, accessible, and properly described in library catalogs and digital repositories. Their work supports searchability, digital preservation, and resource sharing by applying standards and best practices for cataloging. Metadata librarians often collaborate with IT staff, archivists, and subject specialists to enhance user access to library materials.

What skills and qualifications are needed to thrive as a metadata librarian?

To thrive as a Metadata Librarian, you need expertise in cataloging standards (such as MARC, Dublin Core), metadata schema, and information organization, usually supported by a Master's in Library Science or a related field. Familiarity with integrated library systems (ILS), metadata management tools, and knowledge of cataloging software like OCLC Connexion is typical. Attention to detail, analytical thinking, and strong communication skills help ensure accuracy and facilitate collaboration with library staff. These skills and qualities are crucial to maintaining accessible, well-organized digital and print collections that support user discovery and research.

What are common challenges faced by professionals working in a metadata library role, and how can they be addressed?

Professionals in a metadata library role often encounter challenges such as maintaining consistency and accuracy in metadata standards across diverse collections, keeping up with evolving cataloging guidelines, and integrating new technologies or platforms. Addressing these challenges typically involves ongoing training, collaboration with colleagues to develop clear metadata policies, and staying informed about industry best practices. Regular communication with IT teams and subject specialists is also key to ensuring that metadata effectively supports discoverability and access for library users.

What is the difference between Metadata Library vs Metadata Specialist?

AspectMetadata LibraryMetadata Specialist
CredentialsTypically requires a degree in library science, information management, or related fieldsRequires similar credentials, often with additional certifications in data management or information systems
Work EnvironmentLibraries, archives, or information centers managing large metadata collectionsData-driven organizations, digital repositories, or information management teams
Employer & IndustryLibraries, museums, archives, academic institutionsTech companies, publishing, digital content providers
Search & Comparison IntentUnderstanding library metadata management rolesSpecialized data and metadata management tasks

The main difference is that a Metadata Library focuses on managing metadata within library and archival settings, while a Metadata Specialist handles metadata in broader digital and data environments. Both roles require similar credentials but serve different industry needs.

What are popular job titles related to Metadata Library jobs in Michigan?

For Metadata Library jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Metadata Library jobs in Michigan look for?

The top searched job categories for Metadata Library jobs in Michigan are:

What cities in Michigan are hiring for Metadata Library jobs?

Cities in Michigan with the most Metadata Library job openings:

Metadata Library jobs near you
Infographic showing various Metadata Library job openings in Michigan as of August 2026, with employment types broken down into 1% Internship, 78% Full Time, 14% Part Time, 3% Temporary, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Senior, Software Engineer - AutoTagging

Torc Robotics

Ann Arbor, MI • On-site

$119K - $158K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

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

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
The Auto Tagger team is the engine behind our data flywheel, responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios. By mining driving logs for long-tail events, we provide the foundational data required for safe autonomous trucking. Leveraging Pegasus logical layers, this team structures and catalogs findings into an observations database that directly accelerates development across autonomous perception, sensor fusion, and generative simulation testing.
What You'll Do
  • Integrate and deploy automated event-tagger into production pipelines, running and monitoring tagging tasks at scale across petabytes of vehicle log data.
  • Build and maintain the data engineering pipelines that organize, structure, and catalog tagged scenario data into the observations database.
  • Own CI/CD for the Auto Tagger pipeline using GitHub Actions, keeping deployments reliable, tested, and repeatable.
  • Write production grade code in Python across the pipeline, from data ingestion and transformation through model integration and deployment.
  • Build and operate on Databricks for large scale data processing, interactive querying, and pipeline orchestration.
  • Design, deploy, and scale AWS infrastructure (as code) to support high-volume, distributed processing of vehicle log pipelines - working with structured/tagged outputs and metadata.
  • Instrument pipelines with logging, metrics, and alerting; own on-call response for tagging job failures and data quality regressions.
  • Partner with ML engineers on the team to take tagging and classification models from development into a scalable, monitored production pipeline.
  • Ensure data quality and metadata integrity as tagged events move from raw logs into the observations database used by perception, simulation, and systems teams.
  • Troubleshoot and improve pipeline performance, reliability, and cost as data volume and model complexity grow.

What You'll Need to Succeed
  • BS or MS in Computer Science, Engineering, or a related field, with 5+ years of software engineering experience, including production data pipeline or ML infrastructure work.
  • Strong Python skills, with experience building and maintaining production data or ML pipelines.
  • Hands-on CI/CD experience, GitHub Actions required.
  • Required experience with Databricks for large scale data processing and orchestration.
  • Required experience with AWS, including infrastructure-as-code (Terraform or CloudFormation) for provisioning distributed processing infrastructure.
  • Experience processing large scale time series or unstructured datasets.
  • Experience with observability tooling (e.g., Datadog, Grafana, CloudWatch) for production pipeline monitoring and alerting.
  • Experience integrating and deploying ML models into production systems - serving, monitoring, and rollback, not just training.
  • Strong communication skills to work across ML, perception, and simulation teams.

Bonus Points!
  • Familiarity with auto-labeling pipelines, VLMs, or zero-shot classification for scenario extraction.
  • Experience with distributed compute frameworks such as Ray, Spark, or Daft.
  • Familiarity with robotics data formats (ROS bags, MCAP) and columnar storage formats (Parquet, Arrow).
  • Experience with model serving frameworks such as vLLM or SGLang.
  • Familiarity with scenario description standards like Pegasus layers.

Perks of Being a Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: R-102834
Hiring Range for Job Opening
US Pay Range
$160,800-$193,000 USD

Apply