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Machine Learning Intern Remote Jobs in Utah (NOW HIRING)

DataAnnotation

Staff Software Engineer

Salt Lake City, UT · On-site +1

$60/hr

... remote work and setting your own schedule. We are looking for proficient programmers to help ... machine learning, and other engineers -- who are driving real‐world impact in AI development. Our ...

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Machine Learning Intern Remote information

What are the key skills and qualifications needed to thrive as a Machine Learning Intern (Remote), and why are they important?

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a remote Machine Learning Intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What does a Machine Learning Intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries for ML positions can vary based on experience, location, and company, but they tend to be above average compared to many other entry-level roles in technology. Internships in ML may offer lower pay, but full-time positions often provide competitive compensation and benefits.
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Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Orem, UT • Remote

Other

Posted 8 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