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Remote Deep Learning Jobs in Missouri (NOW HIRING)

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

Team members who choose virtual / remote work should have an adequate space to serve as their home ... deep learning models to forecast demand. These models will enable branch-level decision-making ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · Remote

Team members who choose virtual / remote work should have an adequate space to serve as their home ... deep learning models to forecast demand. These models will enable branch-level decision-making ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

Team members who choose virtual / remote work should have an adequate space to serve as their home ... deep learning models to forecast demand. These models will enable branch-level decision-making ...

Jobgether

Strong background in machine learning, deep learning, AI systems, or a closely related technical ... Fully remote work from India. * Opportunity to work on large-scale machine learning models and high ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Block

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

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Remote Deep Learning information

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$23

$53

$80

How much do remote deep learning jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for remote deep learning in Missouri is $53.09, according to ZipRecruiter salary data. Most workers in this role earn between $42.98 and $65.72 per hour, depending on experience, location, and employer.

What is a remote deep learning engineer?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What skills and qualifications are needed to thrive as a remote deep learning engineer?

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.

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

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

What is the difference between Remote Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

What are the most commonly searched types of Deep Learning jobs in Missouri?

The most popular types of Deep Learning jobs in Missouri are:

What are popular job titles related to Remote Deep Learning jobs in Missouri?

For Remote Deep Learning jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Deep Learning jobs in Missouri look for?

The top searched job categories for Remote Deep Learning jobs in Missouri are:

What cities in Missouri are hiring for Remote Deep Learning jobs?

Cities in Missouri with the most Remote Deep Learning job openings:

Remote Deep Learning jobs near you
Infographic showing various Remote Deep Learning job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $110,433 per year, or $53.1 per hour.

Data Scientist

Saint Louis, MO • On-site, Remote

Enterprise Holdings
Travel Arrangement Services • 10K+ employees
Learn more about Enterprise Holdingsexternal

Full-time

Re-posted 2 days ago

Enterprise Holdings rating

7.1

Company rating: 7.1 out of 10

Based on 268 frontline employees who took The Breakroom Quiz

118th of 178 rated vehicle equipment hire

Job description

Overview
ABOUT THE COMPANY
Enterprise Mobility is a leading provider of mobility solutions, owning and operating the Enterprise Rent-A-Car, National Car Rental and Alamo Rent A Car brands through its integrated global network of independent regional subsidiaries. Enterprise Mobility and its affiliates offer extensive car rental, carsharing, truck rental, fleet management, retail car sales, as well as travel management and other transportation services, to make travel easier and more convenient for customers.
Privately held by the Taylor family of St. Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a diverse fleet of 2.4 million vehicles and accounted for nearly $39 billion in revenue through a network of more than 9,500 fully-staffed neighborhood and airport rental locations in more than 90 countries and territories.
As we continue to build a team that drives us forward, we are excited to announce the opening for a Data Scientist.
ABOUT THE ROLE
The Data Scientist is a key driver of innovation, transforming data into actionable insights that improve business processes. In this role, you'll develop cutting-edge analytical products-creating algorithms for automation, building predictive models, designing experiments, and applying causal inference techniques to observational data. You'll also harness mathematical optimization to identify the most profitable business strategies. Success in this position requires strong collaboration with both technical and non-technical teams to ensure the creation, delivery, and adoption of impactful analytical solutions
This position offers the opportunity to work fully remote within the United States (except for Alaska and/or Hawaii). Team members who choose virtual / remote work should have an adequate space to serve as their home office, and must be able to work a schedule within U.S. Central Standard Time core business hours This position will require employees to come on site to one of our St. Louis campus locations a few times per year for meetings/events or as needed. #LI-REMOTE
We are committed to a fair and transparent hiring process. Candidates should expect identity verification, video interviews, technical validation of skills, and verification of employment, education, and work authorization. Falsification of information, proxy interviewing, or misrepresentation of experience or location will result in disqualification.
Responsibilities
As a Data Scientist focused on revenue management, you will design and deploy advanced deep learning models to forecast demand. These models will enable branch-level decision-making, helping maximize revenue by leveraging historical trends and predictive analytics. In this role, you will collaborate closely with cross-functional teams to develop and implement analytical solutions that drive measurable business impact.
  • Collaborate with the team to design and deliver analytical solutions that drive business impact
  • Extract, clean, and manipulate structured and unstructured data from multiple sources
  • Perform exploratory data analysis to identify patterns, trends, and insights
  • Develop predictive models to support data-driven decision-making
  • Design and oversee experiments, ensuring accurate execution and interpretation of results
  • Apply causal inference techniques using observational data to uncover relationships
  • Prepare and deliver clear documentation of methodologies, findings, and recommendations
  • Create and present insightful reports and presentations for technical and non-technical audiences
  • Partner with cross-functional teams to implement and operationalize analytical solutions

Equal Opportunity Employer/Disability/Veterans
Qualifications
Required:
  • Must be presently authorized to work in the U.S. without a requirement for work authorization sponsorship by our company for this position now or in the future
  • Must reside in the United States (does not include Alaska or Hawaii)
  • Must be able to work a schedule within U.S. Central Standard Time core business hours.
  • Must have a Master's Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Must have two (2+) years of experience with predictive models, statistical inference and deep learning
  • Must have experience using libraries like tensorflow or pytorch
  • Must have experience preparing and giving presentations to technical and non-technical audiences
  • Must have proficiency in R or Python
  • Must be committed to incorporating security into all decisions and daily job responsibilities

Preferred:
  • Doctorate Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Experience designing experiments
  • Experience exploring and visualizing data
  • Experience using Linux/Unix
  • Experience using SQL
  • Experience working with data (merging, recording, etc.) from a variety of sources/formats
  • Experience working with observational data to attempt causal inference (e.g. matching, weighting, etc.)

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