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Remote Computer Vision Postdoc Jobs in Arizona (NOW HIRING)

The French Agency

*Remote* Tax Manager in US

Tempe, AZ · On-site +1

$90K - $150K/yr

Big 4 firm experience preferred * Computer proficiency with software programs such as RIA ... Bonus potential up to 10% base of salary * 100% company-paid medical, dental, vision, life, short ...

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Remote Computer Vision Postdoc information

What are some common challenges faced by remote Computer Vision Postdocs, and how can they be addressed?

Remote Computer Vision Postdocs often encounter challenges related to collaboration and access to computational resources. Since much of the work involves large datasets and high-performance computing, ensuring secure and efficient remote access to servers and data is crucial. Effective communication with mentors and team members, often across different time zones, requires proficiency with collaboration tools and proactive scheduling. To address these challenges, it can be helpful to establish regular check-ins, document workflows clearly, and leverage cloud-based platforms for data processing and code sharing.

What is a Remote Computer Vision Postdoc?

A Remote Computer Vision Postdoc is a research position for individuals who have recently completed their Ph.D. and are specializing in the field of computer vision, all while working remotely. These postdoctoral researchers typically conduct advanced studies on topics such as image recognition, object detection, and machine learning algorithms, often collaborating with academic institutions or industry labs. The remote aspect allows for flexible work locations, making it possible to join international teams and contribute to projects from anywhere in the world. This role often emphasizes publishing research, developing prototypes, and contributing to open-source projects.

What are the key skills and qualifications needed to thrive as a Remote Computer Vision Postdoc, and why are they important?

To thrive as a Remote Computer Vision Postdoc, you need a solid background in computer vision, machine learning, and programming, typically supported by a PhD in computer science or a related field. Proficiency with deep learning frameworks (such as TensorFlow or PyTorch), coding languages like Python or C++, and experience with large-scale data processing are essential. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in collaborative, research-driven environments. These competencies ensure you can independently advance research objectives, contribute innovative solutions, and work efficiently with distributed teams.
What are the most commonly searched types of Computer Vision Postdoc jobs in Arizona? The most popular types of Computer Vision Postdoc jobs in Arizona are:
What are popular job titles related to Remote Computer Vision Postdoc jobs in Arizona? For Remote Computer Vision Postdoc jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Computer Vision Postdoc jobs in Arizona look for? The top searched job categories for Remote Computer Vision Postdoc jobs in Arizona are:
What cities in Arizona are hiring for Remote Computer Vision Postdoc jobs? Cities in Arizona with the most Remote Computer Vision Postdoc job openings:
Remote Computer Vision Postdoc jobs near you
Infographic showing various Remote Computer Vision Postdoc job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Re-posted 17 days ago

Job description


Infomatics is partnered with a large retailer that is hiring a Principal AI Data Scientist on a direct hire/FTE basis near Phoenix, AZ. Can work remote. All applicants must be eligible & willing to be hired on W2.

You will lead various AI efforts involving computer vision, deep learning, and nlp in addition to other machine learning model builds. You will not only work on large scale projects to provide value to the customers but are also routinely involved in building our internal R&D capability to have an edge in the analytics industry. You will lead some of the most strategic and very complex problems.
Duties/Responsibilities:
  • Builds and validates machine learning models of high risk/reward problems utilizing large scale data from multiple data sources and methodologies.
  • Uses machine learning techniques to create data-driven solutions for various business use-cases.
  • Writes programs utilizing existing libraries and methodologies.
  • Interprets, communicates, and presents analytic results to C-Level executives and below.
  • Consistently collaborates with fellow data scientists, data engineers, business partners, project managers, cross-functional teams, key stakeholders, and other domains to drive business value.
  • Leads AI best practice sharing opportunities and knowledge of industry trends and innovations in data science.
  • Leads projects with external partners and vendors to develop solutions to meet business needs while resolving any issues that may arise.
  • Contributes to the organization's data strategy and roadmap.
  • Embeds and drives the organization with the most up-to-date AI methodology.
Qualifications:
  • Master's or PhD degree in a quantitative field with 5+ years of data science experience.
  • Applied expertise in artificial intelligence with experience applying natural language processing, computer vision (image processing), and deep leaning. Need to have the capability to leverage current mature mainstream AI application tools and methodology
  • Proficiency in machine learning with familiarity and actual applications of scikit-learn library machine learning techniques such as decision tree, gradient boosting, XGBoost, etc. for regression, classification, or segmentation problems.
  • Programming expertise in Python with familiarity with cloud environments (AWS, Databricks, etc.)
  • Ability to work with large data sets from multiple data sources
  • Ability to communicate complex analytics concepts and techniques to C-Level executives and below
  • Ability to work collaboratively with other data scientists, data engineers, multiple stakeholders across the business, and with external partners
  • Intellectual curiosity, a passion for data, and a results orientation.