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Machine Learning Engineer Jobs in North Dakota (NOW HIRING)

ND · On-site

$73K - $174K/yr

Required Qualification * 2 to 4 years of experience in Software Engineering, Backend Development, Machine Learning, NLP, or related fields. * 1 to 2+ years of hands-on experience working with LLM ...

ND · On-site

$73K - $174K/yr

Required Qualification * 2 to 4 years of experience in Software Engineering, Backend Development, Machine Learning, NLP, or related fields. * 1 to 2+ years of hands-on experience working with LLM ...

ND · On-site

$102 - $177/hr

... machine learning, AI/analytics, and OT cybersecurity. * Familiarity with Industry 4.0 frameworks ... Engineering * Math (STEM) Application * Strategic Thinking Preferred Skills: * Benchmarking

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

ND · On-site

$79 - $127.65/hr

Competence in prompt engineering for multi‑step tasks and chaining prompts to implement simple ... Knowledge of Big Data, data pipelining, machine learning, intermediate level of software ...

Perform engineering duties in planning and designing machines, and other mechanically functioning ... Our dynamic environment offers advanced technology and ongoing learning, placing you at the ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

Showing results 41-60

Machine Learning Engineer information

See North Dakota salary details

$33.3K

$136.2K

$204.7K

How much do machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for machine learning engineer in North Dakota is $136,248.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,400.00 and $164,000.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in North Dakota?

The most popular types of Machine Learning Engineer jobs in North Dakota are:

What are popular job titles related to Machine Learning Engineer jobs in North Dakota?

For Machine Learning Engineer jobs in North Dakota, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in North Dakota look for?

The top searched job categories for Machine Learning Engineer jobs in North Dakota are:

What cities in North Dakota are hiring for Machine Learning Engineer jobs?

Cities in North Dakota with the most Machine Learning Engineer job openings:

What are popular job titles related to Machine Learning Engineer jobs in ND?

For Machine Learning Engineer jobs in ND, the most frequently searched job titles are:

Infographic showing various Machine Learning Engineer job openings in North Dakota as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $136,248 per year, or $65.5 per hour.

Senior Software Engineer

United Airlines

ND • On-site

$73K - $174K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


United Airlines rating

7.9

Company rating: 7.9 out of 10

Based on 342 frontline employees who took The Breakroom Quiz

7th of 26 rated airlines


Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location

This role is a Hybrid opportunity based in New jersey, Atlanta, Chicago, Dallas 

About the job you're considering

At Capgemini, you will collaborate with cross-functional teams to deliver innovative technology solutions that drive business value and enhance client experiences. You will contribute to the design, development, and continuous improvement of scalable, high-quality solutions in a dynamic and collaborative environment.

Overview

We are seeking a highly motivated Conversational AI Engineer with experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and NLP-based solutions. The ideal candidate will have hands-on experience building, deploying, and optimizing AI-powered applications while collaborating with cross-functional stakeholders to solve complex business problems.

Key Responsibilities
  • Design, develop, and deploy conversational AI solutions using Large Language Models (LLMs) such as OpenAI, Anthropic, and Hugging Face models.
  • Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines to improve response quality and domain-specific knowledge retrieval.
  • Conduct model evaluation, prompt engineering, and performance testing to ensure high-quality AI outputs.
  • Collaborate with business stakeholders, product teams, and developers to translate business requirements into scalable AI solutions.
  • Develop NLP-powered applications involving text parsing, classification, sentiment analysis, summarization, and text generation.
  • Manage end-to-end AI application deployment on cloud platforms, with a focus on AWS and cloud-native architectures.
  • Deploy and manage AI workloads using containerization and orchestration technologies such as Docker and Kubernetes.
  • Design and implement data preparation workflows, including data cleaning, labeling, augmentation, and synthetic data generation.
  • Monitor, troubleshoot, and optimize AI systems in production environments.
  • Implement AI governance, scalability, and reliability best practices.
  • Work with MCP (Model Context Protocol) frameworks and related integrations for AI application deployment and orchestration.
Required Qualification
  • 2 to 4 years of experience in Software Engineering, Backend Development, Machine Learning, NLP, or related fields.
  • 1 to 2+ years of hands-on experience working with LLM APIs such as OpenAI, Anthropic, Azure OpenAI, or Hugging Face models.
  • Proven experience building and deploying RAG-based applications.
  • Strong understanding of prompt engineering, model evaluation techniques, and AI application lifecycle management.
  • Experience working directly with business stakeholders and managing technical requirements.
  • Proficiency in Python and relevant AI/ML libraries and frameworks.
  • Strong understanding of NLP concepts and transformer-based architectures (GPT, BERT, Llama, etc.).
  • Experience with vector databases, embeddings, semantic search, and retrieval systems.
  • Knowledge of cloud platforms, preferably AWS, for deploying and managing AI applications.
  • Hands-on experience with Docker and Kubernetes for scalable application deployment.
  • Experience in data preprocessing, augmentation, and synthetic data generation techniques.
  • Excellent analytical thinking and problem-solving skills.
Preferred Qualification
  • Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks.
  • Experience deploying applications using MCP (Model Context Protocol).
  • Familiarity with MLOps practices, CI/CD pipelines, and model monitoring.
  • Understanding of observability, security, and governance practices for AI systems.
  • Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Azure AI Search.

The base compensation range for this role in the posted location is: $73,150 to $174,000

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect.  We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States.  http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.


What United Airlines employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


United Airlines logo

About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

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