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Remote Prompt Engineering Jobs in Hawaii (NOW HIRING)

Vultus Inc

Machine Learning Engineer

Honolulu, HI · On-site +1

$110K - $145K/yr

Familiarity with prompt engineering and Retrieval-Augmented Generation (RAG). * Experience with Agile/Scrum methodologies. Experience 3-6 Years Employment Type Full-Time Work Location Remote / Hybrid ...

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Remote Prompt Engineering information

How to make $1000 a week remotely?

Remote prompt engineering can generate $1000 or more weekly by freelancing on platforms like Upwork or Fiverr, building a strong portfolio, and offering specialized skills in AI and NLP. Consistent work, high-demand projects, and efficient time management are key to reaching this income level.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and working in high-demand industries or companies. Compensation often includes base salary, bonuses, and stock options, particularly in tech giants or startups with significant growth potential.

What is the difference between Remote Prompt Engineering vs Remote Data Annotation Specialist?

AspectRemote Prompt EngineeringRemote Data Annotation Specialist
Required CredentialsBasic understanding of AI, NLP, and scripting skillsAttention to detail, familiarity with annotation tools, no formal certifications required
Work EnvironmentCollaborative with AI/ML teams, remote setupIndependent annotation tasks, remote or on-site
Industry UsageAI development, NLP projects, machine learningData labeling for AI training datasets
Search & Comparison IntentUnderstanding roles in AI development, job requirementsData labeling jobs, annotation tasks, related roles

Remote Prompt Engineering involves designing and refining prompts for AI models, requiring some technical skills and collaboration with AI teams. In contrast, Remote Data Annotation Specialists focus on labeling data to train AI systems, emphasizing attention to detail. Both roles are essential in AI development but differ in skills and daily tasks.

What are some common challenges faced by remote prompt engineers, and how can they be addressed?

Remote prompt engineers often face challenges related to communication and collaboration, especially when working across time zones and with interdisciplinary teams. Staying updated on rapidly evolving AI technologies and understanding nuanced user requirements can also be demanding. To address these, prompt engineers can leverage collaborative tools, maintain clear documentation, and participate in regular team syncs. Building a habit of continuous learning and engaging in knowledge-sharing sessions helps keep skills relevant and fosters a sense of connection despite remote work.

What are the key skills and qualifications needed to thrive as a Remote Prompt Engineer, and why are they important?

To thrive as a Remote Prompt Engineer, you need a strong background in natural language processing, programming (often Python), and an understanding of AI/ML concepts, typically supported by a relevant degree or industry experience. Familiarity with large language models (like OpenAI's GPT), prompt optimization tools, and version control systems such as Git is common. Creativity, problem-solving, and strong written communication are vital soft skills for designing effective prompts and collaborating remotely. These skills ensure the development of high-performing AI solutions and seamless teamwork in distributed environments.

Are prompt engineers still in demand?

Prompt engineering is a growing field as organizations seek professionals skilled in designing effective prompts for AI language models. Demand for prompt engineers is increasing across industries such as technology, healthcare, and finance, often requiring knowledge of AI tools and natural language processing. The role is expected to remain relevant as AI adoption expands.

What jobs make $3,000 a day?

High-paying jobs such as remote prompt engineering, specialized consulting, or executive roles can earn $3,000 or more per day, especially for professionals with advanced skills, experience, and in-demand expertise. These roles often require strong technical knowledge, certifications, and the ability to deliver high-value services on a freelance or contract basis.

What is remote prompt engineering?

Remote prompt engineering is the practice of designing and refining prompts for AI language models, such as ChatGPT, while working from a remote location. Prompt engineers craft instructions or questions to optimize the model’s responses for specific tasks or applications. This role typically involves understanding both the capabilities and limitations of AI systems, as well as the needs of end users or clients. Remote prompt engineers collaborate online with teams and may work for tech companies, research organizations, or as independent contractors.
What are popular job titles related to Remote Prompt Engineering jobs in Hawaii? For Remote Prompt Engineering jobs in Hawaii, the most frequently searched job titles are:
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What cities in Hawaii are hiring for Remote Prompt Engineering jobs? Cities in Hawaii with the most Remote Prompt Engineering job openings:
Remote Prompt Engineering jobs near you
Infographic showing various Remote Prompt Engineering job openings in Hawaii as of July 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Vultus Inc

Honolulu, HI • On-site, Remote

$110K - $145K/yr

Full-time

Posted 3 days ago

Job description

Machine Learning EngineerJob Summary

We are looking for a talented Machine Learning Engineer to design, develop, and deploy scalable machine learning models that solve complex business problems. The ideal candidate should have experience in data preprocessing, model development, feature engineering, and deploying ML solutions in production environments. You will work closely with data scientists, software engineers, and product teams to build intelligent applications.

Key Responsibilities
  • Design, build, and deploy machine learning models for predictive analytics and automation.
  • Collect, clean, and preprocess structured and unstructured datasets.
  • Perform feature engineering and model optimization to improve performance.
  • Train, validate, and evaluate machine learning models using industry best practices.
  • Deploy ML models using cloud platforms and containerization technologies.
  • Monitor model performance and retrain models as needed.
  • Collaborate with cross-functional teams to understand business requirements.
  • Develop APIs and services for model inference.
  • Document model architecture, experiments, and deployment processes.
  • Stay updated with the latest advancements in AI and machine learning technologies.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • 3–6 years of experience in Machine Learning or Artificial Intelligence.
  • Strong programming skills in Python.
  • Experience with supervised and unsupervised learning algorithms.
  • Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
  • Knowledge of statistics, probability, and linear algebra.
  • Experience with SQL and NoSQL databases.
  • Familiarity with REST APIs and microservices architecture.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Understanding of CI/CD pipelines for ML deployment.
Primary Skills
  • Python
  • Machine Learning
  • Deep Learning
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Pandas
  • NumPy
  • Feature Engineering
  • Model Deployment
  • Data Preprocessing
  • SQL
  • Docker
  • Kubernetes
  • Git
Secondary Skills
  • NLP (Natural Language Processing)
  • Computer Vision
  • MLOps
  • Apache Spark
  • MLflow
  • Airflow
  • Kafka
  • Azure ML
  • AWS SageMaker
  • Google Vertex AI
  • FastAPI
  • Flask
Preferred Qualifications
  • Experience with large-scale ML model deployment.
  • Knowledge of Generative AI and Large Language Models (LLMs).
  • Experience with vector databases such as Pinecone, Milvus, or FAISS.
  • Familiarity with prompt engineering and Retrieval-Augmented Generation (RAG).
  • Experience with Agile/Scrum methodologies.
Experience

3–6 Years

Employment Type

Full-Time

Work Location

Remote / Hybrid / On-site

Salary Range

$110,000 – $145,000 per year (Based on experience and location)