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Remote Machine Learning Ops Engineer Jobs in Hawaii

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 ...

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

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 ...

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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Remote Machine Learning Ops Engineer information

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Infographic showing various Remote Machine Learning Ops Engineer job openings in Hawaii as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.

Machine Learning Engineer

Vultus Inc

Honolulu, HI • On-site, Remote

$110K - $145K/yr

Full-time

Posted 16 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)