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Remote Machine Learning Jobs in Honolulu, HI (NOW HIRING)

Vultus Inc

Machine Learning Engineer

Honolulu, HI · On-site +1

$110K - $145K/yr

Machine Learning EngineerJob Summary We are looking for a talented Machine Learning Engineer to ... Experience 3-6 Years Employment Type Full-Time Work Location Remote / Hybrid / On-site Salary Range ...

micro1 AI

AI Trainer - Microbiology Expert

Honolulu, HI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Booz Allen Hamilton, Inc.

Data Engineer

Honolulu, HI · On-site +1

$113K - $135K/yr

Remote Work: No Job Number: R0244293 Location: Honolulu,HI,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

Booz Allen Hamilton, Inc.

Data Engineer

Honolulu, HI · On-site +1

$113K - $135K/yr

Remote Work: No Job Number: R0240103 Location: Honolulu,HI,US Share job via: Share Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Honolulu, HI

Remote Machine Learning information

See Honolulu, HI salary details

$25.2K

$42.1K

$86.9K

How much do remote machine learning jobs pay per year?

As of Aug 9, 2026, the average yearly pay for remote machine learning in Honolulu, HI is $42,056.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Honolulu, HI? The most popular types of Machine Learning jobs in Honolulu, HI are:
What are popular job titles related to Remote Machine Learning jobs in Honolulu, HI? For Remote Machine Learning jobs in Honolulu, HI, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Honolulu, HI look for? The top searched job categories for Remote Machine Learning jobs in Honolulu, HI are:
What cities near Honolulu, HI are hiring for Remote Machine Learning jobs? Cities near Honolulu, HI with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Honolulu, HI as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $42,056 per year, or $20.2 per hour.

Machine Learning Engineer

Vultus Inc

Honolulu, HI • On-site, Remote

$110K - $145K/yr

Full-time

Posted 19 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)