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Ai Labelling Jobs in Minnesota (NOW HIRING)

Sr Data Engineer BI

Bloomington, MN · On-site

$110K - $150K/yr

AI/ML Development & Agentic Workflows [15%] * Design, develop, train, and deploy machine learning ... Partner with InfoSec to implement role-based access, row-level security, and sensitivity labeling ...

Check and change label rolls throughout the day to ensure continuity. Essential Skills ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

Verify that outside labels and unit labels match for all packet parts. * Perform daily and weekly ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

Assembler

New Ulm, MN · On-site

$17/hr

Verify that outside labels and unit labels match for all packet parts. * Perform daily and weekly ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

Panel Builder

Eden Prairie, MN · On-site

$27.06 - $35.22/hr

Service teMotion Ai (MN72) 7350 Golden Triangle Drive Eden Prairie, MN 55344 Job Title: Electrical ... Cut, strip, crimp, label, and terminate wires according to specifications. * Ensure proper routing ...

BI Application Manager

Bloomington, MN · Hybrid

$140K - $150K/hr

Partner with InfoSec on role-based access, row-level security, and sensitivity labeling for data ... Innovation, AI & Agentic Analytics [10%] * Champion innovation by evaluating, prototyping, and ...

Food Scientist

Detroit Lakes, MN · On-site

$55K - $85K/yr

... labeling needs, and translate these into practical formulation solutions. * Support customer ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

New

... labeling needs, and translate these into practical formulation solutions. * Support customer ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

New

Food Scientist

Detroit Lakes, MN · On-site

$55K - $85K/yr

... labeling needs, and translate these into practical formulation solutions. * Support customer ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

New

Design and implement Microsoft Purview solutions (e.g., sensitivity labeling strategies, advanced ... Build awareness and controls for emerging AI and agentic AI security considerations (e.g., Security ...

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Data Center Technician

Eagan, MN · On-site

$30 - $40/hr

Organize, route, and label data and power cables to maintain a clean, efficient, and safe ... Whether you're looking to expand your experience in data centers, AI infrastructure, field services ...

... labeling product for outbound shipment Qualifications: -Willing to learn new skills and gain ... AI helps assess applications and qualifications, but final decisions are made by our hiring team.

Showing results 21-40

Ai Labelling information

What are some typical challenges faced in AI labelling roles and how can they be managed?

One common challenge in AI Labelling roles is maintaining accuracy and consistency when labeling large volumes of data according to detailed guidelines, which can become repetitive or mentally taxing. Managing these challenges often involves taking regular breaks, double-checking work, and staying up-to-date with any updates to annotation standards provided by the team. Collaborating with supervisors and peers to clarify uncertainties and seek feedback also helps ensure high-quality output. Over time, professionals in this role often develop efficient workflows and a keen eye for detail, opening doors to advancement into quality assurance or project coordination positions within the data annotation field.

What is an AI labelling?

An AI labelling job involves annotating data—such as images, text, audio, or video—to help train machine learning models. This process includes tasks like tagging objects in images, transcribing speech, or categorizing text. The labelled data is crucial for AI systems to learn and make accurate predictions. These jobs are commonly found in industries like tech, healthcare, and autonomous driving. Attention to detail and consistency are key skills for this role.

What are the key skills and qualifications needed to thrive in AI labelling?

To thrive in an AI Labelling role, you need attention to detail, basic data analysis skills, and the ability to follow complex guidelines, with many roles requiring at least a high school diploma or equivalent. Familiarity with data annotation tools, image or text labeling platforms, and sometimes basic scripting or database systems is beneficial. Strong communication, time management, and the ability to work both independently and as part of a team are valuable soft skills. These competencies ensure the consistent and accurate labeling of data, which is critical for training high-quality AI and machine learning models.

What are popular job titles related to Ai Labelling jobs in Minnesota? For Ai Labelling jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Ai Labelling jobs in Minnesota look for? The top searched job categories for Ai Labelling jobs in Minnesota are:
Infographic showing various Ai Labelling job openings in Minnesota as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Sr Data Engineer BI

Quality Bicycle Products

Bloomington, MN • On-site

$110K - $150K/yr

Full-time

Re-posted 2 days ago


Quality Bicycle Products rating

9.0

Company rating: 9.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

25th of 412 rated retail wholesalers


Job description

This is a Hybrid role that is based in the Bloomington, MN Metro area. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.
WHAT YOU WILL BE ACCOUNTABLE FOR:
The Senior Data Engineer is a hands-on technical leader responsible for designing, building, and evolving QBP's modern data platform that powers Business Intelligence, AI, and advanced analytics across the enterprise. This role bridges current-state SAP Data Services and SQL Server data warehousing with the future-state Microsoft Fabric / OneLake lakehouse architecture, while integrating data from QBP's complex enterprise landscape including SAP S/4HANA, HighJump WMS, Anaplan, Prophix, Sales Cloud, and eCommerce. Beyond traditional data engineering, this role will lead the development of AI/ML capabilities - building machine learning models, designing and automating AI agents, and operationalizing agentic workflows that augment business decision-making. The Senior Data Engineer is expected not only to deliver, but to innovate evaluating emerging technologies, championing modern data engineering practices, and shaping the architectural direction of QBP's data and AI platform.
Technical Leadership & Architecture [25%]
  • Own the end-to-end data architecture for key BI domains, including ingestion, storage, transformation, semantic modeling, and serving layers.
  • Lead design and implementation of QBP's medallion (Bronze/Silver/Gold) architecture on Microsoft Fabric / OneLake, integrating with the SQL Server data warehouse during the modernization transition.
  • Set and enforce data engineering standards including coding practices, version control, code reviews, and automated testing.
  • Serve as the technical escalation point for complex data engineering challenges across the BI team.

Data Pipeline Development & ETL/ELT [20%]
  • Design, build, and optimize scalable, resilient, and idempotent [LP1.1][SB1.2][LP1.3]data pipelines using Azure Data Factory, Fabric Data Pipelines, SAP Data Services (current state), Python/PySpark, and SQL.
  • Lead the migration of legacy ETL workloads (SAP Data Services, AWS SQL Server) into modern Azure/Fabric patterns as part of the S/4HANA transformation.
  • Implement change-data-capture (CDC), incremental loads, retry-safe backfills, and data quality checks across pipelines.
  • Integrate data from SAP S/4HANA, HighJump WMS, Anaplan, Sales Cloud, ShipERP, and external partner feeds into the analytics platform.

AI/ML Development & Agentic Workflows [15%]
  • Design, develop, train, and deploy machine learning models to support forecasting, anomaly detection, classification, and recommendation use cases across QBP's business domains.
  • Build, configure, and automate AI agents and agentic workflows (e.g., Microsoft Copilot Studio, Azure AI Foundry, LangChain/LangGraph, or equivalent) that integrate with QBP's enterprise systems and data platform.
  • Operationalize ML models and AI agents through MLOps practices - model versioning, monitoring, drift detection, and automated retraining pipelines.
  • Partner with business stakeholders to identify high-value AI/ML opportunities and translate them into production-grade solutions.
  • Champion responsible AI practices, ensuring solutions are explainable, secure, and aligned with QBP's data governance standards.

Innovation & Emerging Technology [10%]
  • Champion innovation by evaluating, prototyping, and recommending emerging data and AI technologies (e.g., Microsoft Fabric, SAP BDC/DataSphere, Databricks, Delta Sharing, real-time analytics, LLM-based agents).
  • Lead Proof-of-Concepts (POCs) to validate new tools and patterns (e.g., Fabric Lakehouse POC, agentic AI workflows), with clear milestones and documentation.
  • Stay current on industry trends in DataOps, data mesh, lakehouse architectures, and AI-augmented data engineering.
  • Identify and pilot AI/Copilot capabilities in Power BI and Fabric to accelerate analytics delivery.

Data Governance, Quality & Reliability [10%][LP2.1][SB2.2][LP2.3]
  • Implement data quality, lineage, cataloging, and master data management practices.
  • Implement monitoring, observability, and freshness for critical data pipelines and datasets.
  • Partner with InfoSec to implement role-based access, row-level security, and sensitivity labeling for data assets.
  • Perform proactive monitoring and root-cause analysis for refresh and ETL failures.

Mentorship & Cross-Functional Collaboration [10%]
  • Mentor and coach data engineers and BI developers; provide technical guidance, code reviews, and design feedback.
  • Collaborate with the SAP, WMS, eCommerce, Security, and Cloud Infrastructure teams to align on timelines, dependencies, and architectural direction.
  • Partner with business stakeholders to translate analytics and AI requirements into scalable data solutions.

Operational Support & Production Stewardship [10%]
  • Provide expert-level support for production data pipelines, dataset refreshes, and BI platform stability.
  • Lead incident response and root-cause analysis for high-severity BI issues.
  • Drive continuous improvement in deployment, documentation, and code review standards.

*Represents essential duties. Other tasks and responsibilities as assigned.
WHAT YOU NEED TO SUCCEED:
REQUIRED QUALIFICATIONS:
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
  • 8+ years of progressive experience in data engineering, business intelligence, or analytics platform development.
  • Expert-level SQL (T-SQL, PL/SQL): complex queries, stored procedures, window functions, partitioning, performance tuning.
  • 5+ years designing and building ETL/ELT pipelines with tools such as Azure Data Factory, SAP Data Services, Fabric Data Pipelines, or equivalent.
  • Strong understanding of dimensional modeling (star/snowflake schemas, slowly-changing dimensions) and modern lakehouse / medallion architecture patterns.
  • Proven experience integrating BI/data platforms with enterprise COTS systems - SAP (ECC, S/4HANA, or BW), HighJump WMS, Anaplan, or equivalent.
  • Experience with Power BI semantic modeling and DAX.
  • Demonstrated experience leading technical design, mentoring engineers, and driving best practices.
  • Excellent communication skills with the ability to translate complex technical concepts for both technical and non-technical stakeholders.

PREFERRED QUALIFICATIONS:
  • Degree in Data Science, Analytics, Computer Science, or related field.
  • 3+ years programming experience in Python and/or PySpark for data engineering and ML workloads.
  • Hands-on experience building and deploying machine learning models (scikit-learn, TensorFlow, PyTorch, Azure ML, or Fabric Data Science).
  • Experience designing and automating AI agents and agentic workflows using frameworks such as Microsoft Copilot Studio, Azure AI Foundry, or equivalent.
  • Familiarity with LLM integration patterns (RAG, function/tool calling, prompt engineering) and vector databases.
  • Experience with MLOps practices and tooling.
  • Experience with ETL tools (CDS Views, BDC, DataSphere, Theobald Xtract Universal, or dab Nexus).
  • Experience with streaming/real-time data (Kafka, Event Hubs, Fabric Real-Time Intelligence, or Spark Structured Streaming).
  • Experience with DataOps / CI-CD for data.
  • Familiarity with Microsoft Purview or other data governance/cataloging platforms.
  • Working knowledge of AWS/Fabric for cross-cloud integration.
  • Experience with Agile/Scrum methodologies.

OTHER RELATED CRITERIA:
Physical Requirements
  • Ability to perform work on a phone and computer extensively.

Model QBP Core Values
  • Act with integrity
  • Be a true partner
  • Create something special
  • Deliver greatness
  • Keep the customer first

As a senior technical leader, believe in and serve as a role model for Q's DEI mission by creating a work environment where everyone has respect, space, a voice, and can thrive.
Quality Bicycle Products is a proud certified B-Corp and an Equal Employment Opportunity employer committed to diversity, equity, and inclusion. We welcome talent from all backgrounds and encourage employees to bring their authentic selves to work. We do not discriminate based on race, color, religion, national origin, sex (including pregnancy and related conditions), sexual orientation, gender identity or expression, age, veteran status, disability, genetic information, political views or activity, or any other protected characteristic.
At Quality Bicycle Products, we approach pay ethically and transparently. Our pay ranges are informed by third-party market data and aligned with internal equity across similar roles. Individual pay within these ranges may vary based on skills, experience, performance, tenure, and budget considerations.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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