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Entrylevel Machine Learning Engineer Jobs in North Dakota

Three Point Solutions

Product Engineer

Fargo, ND · On-site

$34 - $36/hr

Heavy Machine Manufacturing Company Duration: 24 Months (Possibility of Extension/Conversion ... Support product development, testing, and design activities as an entry-level electronics engineer.

Three Point Solutions

Manufacturing Engineer

Fargo, ND · On-site

$36 - $38/hr

Heavy Machine Manufacturing Company Location: Fargo, ND 58102 Duration: 24 Months (Possible ... Entry-level Manufacturing Engineer supporting assembly operations, BOM management, and process ...

Apave

756 - NDE Engineer - Bismarck, ND.

Bismarck, ND · On-site

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 ...

Koerber

Mechanical Engineering Intern

Fargo, ND

$18.50 - $24.75/hr

You will provides production support to the machining area and the assembly area * You will support ... You have display entry level skill in Pro/Engineer software * You have demonstrate computer ...

Körber Group

Mechanical Engineering Intern

Fargo, ND · On-site

$18.50 - $24.75/hr

You have display entry level skill in Pro/Engineer software * You have demonstrate computer ... to high-tech machinery and process equipment. Körber combines deep domain expertise with ...

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All JobsEntrylevel Machine Learning Engineer JobsEntrylevel Machine Learning Engineer Jobs in North Dakota

Entrylevel Machine Learning Engineer information

Can I get into AI with no experience?

Entry-level machine learning engineer roles typically require some background in programming, mathematics, and data analysis, but many employers are open to candidates with foundational skills and a willingness to learn. Gaining experience through online courses, projects, and certifications in tools like Python and machine learning frameworks can help you qualify for such positions. Building a portfolio and understanding core concepts can improve your chances of entering the AI field without prior professional experience.

What engineers make $500,000?

Highly experienced senior engineers in fields such as software engineering, data engineering, and machine learning engineering can earn $500,000 or more annually, especially with bonuses, stock options, or in high-cost-of-living areas. Achieving this level typically requires advanced skills, extensive experience, and often leadership roles or specialized expertise in high-demand technologies.

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

AspectEntrylevel Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Math, or related; some knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, implements algorithms, collaborates with engineering teamsAnalyzes data, builds statistical models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles involve working with data and algorithms, an Entrylevel Machine Learning Engineer primarily focuses on developing and deploying machine learning models within software systems. In contrast, a Data Scientist emphasizes analyzing data, creating statistical models, and deriving insights. Both roles often require similar educational backgrounds, but their day-to-day tasks and industry applications differ.

Can I learn ML in 3 months?

As an entry-level machine learning engineer, gaining foundational knowledge in ML within three months is possible with intensive study, focusing on programming (Python), algorithms, and tools like scikit-learn or TensorFlow. However, developing deep expertise and practical experience typically requires longer, ongoing learning and project work.

Which 5 jobs will survive AI?

For entry-level machine learning engineers, roles that require complex problem-solving, creativity, and human judgment—such as data science, AI ethics, research scientist, AI product management, and specialized software development—are likely to persist despite AI advancements. These positions often involve designing, overseeing, and interpreting AI systems, which require deep domain knowledge and critical thinking that AI tools currently cannot fully replicate.
What cities in North Dakota are hiring for Entrylevel Machine Learning Engineer jobs? Cities in North Dakota with the most Entrylevel Machine Learning Engineer job openings:
Entrylevel Machine Learning Engineer jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Bismarck, ND • Remote

Other

Posted 24 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply