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Remote Aws Machine Learning Jobs in Arizona (NOW HIRING)

Lead Security Architect

Phoenix, AZ · Remote

$64.50 - $83.50/hr

Support enterprise initiatives involving AI, Machine Learning, and cloud-native technologies ... AWS Certified Security Specialty TOGAF SABSA * GIAC Security Certifications What We're Looking For ...

Design and develop scalable AI solutions using machine learning models and tools * Ensure the ... Awareness of cloud platforms (AWS, Azure, GCP) and services like S3, EC2, or SageMaker. Analytical ...

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Develop machine learning and generative AI models that ship as customer-facing product features

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Remote Aws Machine Learning information

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

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are remote AWS Machine Learning jobs?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

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

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

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

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are the most commonly searched types of Aws Machine Learning jobs in Arizona? The most popular types of Aws Machine Learning jobs in Arizona are:
What cities in Arizona are hiring for Remote Aws Machine Learning jobs? Cities in Arizona with the most Remote Aws Machine Learning job openings:
AI/ML Engineer - Computer Vision

AI/ML Engineer - Computer Vision

Prime Solutions Group, Inc.

Goodyear, AZ • On-site, Remote

$110K - $180K/yr

Other

Posted 7 days ago


Job description

Description

Prime Solutions Group (PSG), Inc. is an innovative digital engineering company founded in 2007 and headquartered in Goodyear, AZ. We specialize in advanced sensing, AI/ML, and digital engineering solutions, partnering with many of the nation's leading defense companies to deliver mission-critical technology.


Our work spans the full system lifecycle-from R&D to operational deployment-supporting the Department of Defense, Intelligence Community, and federal partners. At PSG, you'll join a small, agile team where your contributions have a direct impact while working alongside top-tier engineering talent



Position Description:

Develop AI-Powered Computer Vision Solutions for Real-World Mission Applications

Prime Solutions Group (PSG), Inc. is seeking an experienced AI/ML Computer Vision Engineer to design, develop, and deploy advanced computer vision and machine learning solutions supporting mission-critical national security programs.


In this role, you will work at the forefront of artificial intelligence, applying state-of-the-art deep learning techniques to challenging real-world problems involving image, video, and sensor data. You will be responsible for developing and optimizing machine learning models, conducting experimentation, improving model performance, and transitioning AI capabilities into operational environments.


This position is ideal for engineers who enjoy solving complex technical challenges, working with large-scale datasets, and turning cutting-edge research into production-ready solutions.

Responsibilities include: 

  • Design, develop, train, and deploy machine learning and computer vision models for real-world mission applications.
  • Build and optimize deep learning architectures, including CNNs, Vision Transformers (ViTs), and hybrid AI/ML models.
  • Perform hyperparameter tuning, model optimization, and performance evaluation to improve accuracy, robustness, and efficiency.
  • Develop and maintain training, validation, testing, and inference pipelines for AI/ML systems.
  • Analyze model performance, identify failure modes, and implement improvements to increase reliability and generalization.
  • Work with large image, video, and sensor datasets to support object detection, classification, segmentation, tracking, and anomaly detection tasks.
  • Collaborate with software engineers and MLOps teams to integrate models into production environments.
  • Evaluate emerging AI technologies and recommend new approaches that improve mission outcomes.
  • Create technical documentation, experiment reports, and performance assessments.
  • Support technical reviews, customer briefings, and cross-functional engineering efforts.  

Requirements

  • U.S. Citizenship
  • Active Top-Secret Clearance with eligibility to obtain an SCI with CI Poly
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Applied Mathematics, or a related technical field.
  • 4+ years of experience developing AI/ML solutions in production, research, or applied engineering environments.
  • Proven experience delivering models using Python and ML frameworks (TensorFlow, PyTorch, Keras, etc.).
  • Experience training and evaluating machine learning models using large datasets. 
  • Experience developing and training computer vision models using deep learning techniques.
  • Familiarity with CNNs, Vision Transformers, object detection, classification, and segmentation.
  • Experience with model tuning, hyperparameter optimization, and performance evaluation.
  • Strong understanding of computer vision fundamentals and image analysis techniques.
  • Ability to improve model accuracy, robustness, and operational performance.
  • Familiarity with software engineering best practices, Git, and collaborative development workflows. 


  Preferred Skills or Experience:

  • Experience with generative AI technologies, including diffusion models and image generation systems.
  • Familiarity with Vision-Language Models (VLMs), multimodal AI, Large Vision Models (LVMs), and Retrieval-Augmented Generation (RAG).
  • Experience with object tracking, multi-object tracking, or video analytics.
  • Experience applying computer vision techniques to imagery, remote sensing, or sensor-based data.
  • Familiarity with reinforcement learning or autonomous systems.
  • Experience with MLOps tools and practices, including Docker, Kubernetes, MLflow, Airflow, and CI/CD pipelines.
  • Experience deploying AI/ML solutions in AWS, Azure, or Google Cloud environments.
  • Experience supporting defense, intelligence, aerospace, or other mission-critical programs.


Why Join PSG?

At PSG, you'll work on challenging AI   problems that directly support national security missions. You'll have the   opportunity to collaborate with highly skilled engineers and researchers   while helping shape the next generation of intelligent sensing, computer   vision, and AI-enabled systems.

We offer:

  • Competitive compensation and   benefits
  • Professional development and tuition   assistance
  • Flexible and collaborative   engineering culture
  • Exposure to cutting-edge AI/ML   technologies
  • Direct impact on mission-critical   programs
  • Opportunities to grow into technical   leadership roles

Bring your passion for AI, computer vision,   and machine learning to PSG and help build the next generation of intelligent   mission systems.



Salary Description

Salary range starts at $110,000 with the potential for higher compensation based on experience, skills, and mission needs