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Ai Data Training Jobs in Minnesota (NOW HIRING)

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations ... Deliver governed datasets and feature engineering/serving for ML training and real-time inference ...

Build relationships with key stakeholders and support user adoption through training, communication, and change management activities. * Support AI-enabled, digital, data, and automation initiatives ...

Build relationships with key stakeholders and support user adoption through training, communication, and change management activities. * Support AI-enabled, digital, data, and automation initiatives ...

Develop documentation, standards, and training to help technical and business users effectively leverage the organization's data and AI capabilities. Serve as a technical bridge between business ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... specialized training and/or progressively responsible work experience in technology for each ...

Drive adoption through demos, enablement, training, and change management initiatives; incorporate ... Collaborate with the AI COE to embed responsible AI practices into the product lifecycle (data ...

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Ai Data Training information

What is AI data training?

AI data training refers to the process of teaching artificial intelligence systems, such as machine learning models, to recognize patterns and make decisions by feeding them large amounts of labeled data. This involves collecting, annotating, and preprocessing data so that the AI can learn from examples and improve its performance over time. Data trainers play a crucial role in ensuring that the data used is accurate, diverse, and relevant to the AI's intended tasks. Effective AI data training helps models become more accurate, reliable, and capable of handling real-world scenarios.

What are the key skills and qualifications needed to thrive as an AI data trainer, and why are they important?

To thrive as an AI Data Trainer, you need a solid understanding of data annotation, machine learning fundamentals, and attention to detail, often backed by experience in data science or a related field. Familiarity with data labeling tools, annotation platforms, and version control systems is typically required. Strong analytical thinking, communication skills, and the ability to follow complex guidelines set top performers apart in this role. These skills ensure that high-quality, accurate datasets are produced to effectively train and improve AI models.

What are some common challenges faced in AI data training roles, and how can they be effectively managed?

Professionals in AI Data Training often encounter challenges such as ensuring data accuracy, managing large and potentially unstructured datasets, and maintaining consistency in labeling. These challenges can be managed through rigorous quality control checks, adopting clear annotation guidelines, and utilizing collaborative tools that streamline the review process. Being detail-oriented and communicating effectively with data scientists and engineers also helps in resolving ambiguities and improving overall data quality.

What is the difference between Ai Data Training vs Data Analyst?

AspectAi Data TrainingData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and other industries
Employer & Industry UsagePrimarily in AI development and machine learning projectsAcross various sectors analyzing data to inform decisions

Ai Data Training involves preparing and labeling data for AI models, focusing on machine learning algorithms. Data Analysts interpret data to generate insights for business decisions. While both roles work with data, Ai Data Training is more technical and model-focused, whereas Data Analysts focus on analysis and reporting.

What job categories do people searching Ai Data Training jobs in Minnesota look for?

The top searched job categories for Ai Data Training jobs in Minnesota are:

What cities in Minnesota are hiring for Ai Data Training jobs?

Cities in Minnesota with the most Ai Data Training job openings:

Infographic showing various Ai Data Training job openings in Minnesota as of August 2026, with employment types broken down into 84% Full Time, and 16% Contract. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution.

Forward Deployed Engineer, Microsoft AI & Data

Minneapolis, MN


Deloitte
Finance and Insurance • 10K+ employees

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services

Good employer

Recommended by students

Paid breaks


$119K - $143K/yr

Full-time

Re-posted 20 days ago


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Microsoft AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Microsoft AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:


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