ZipRecruiter

Log In

2

Remote Deep Learning Jobs in Missouri (NOW HIRING)

Jobgether

$80K - $110K/yr

Join a fully remote, mission-driven climate technology environment where machine learning and ... Develop and deploy new vegetation intelligence products using machine learning, deep learning ...

Jobgether

$94K - $124K/yr

... remote sensing data, and geospatial technologies. This is an ideal opportunity for an experienced ... Practical experience developing deep learning solutions using frameworks such as PyTorch and/or ...

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 ...

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 ...

Bunge North America

Data Scientist

Chesterfield, MO · On-site +1

Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep learning for statistical modeling. Experience with big data technologies and cloud-based data platforms ...

Bunge

Data Scientist

Chesterfield, MO · On-site +1

Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep learning for statistical modeling. Experience with big data technologies and cloud-based data platforms ...

Catawiki

Being pragmatic when needed but also able to go deep into a problem, applying your expert knowledge ... Where you'll be This role is based in Amsterdam but we can offer remote work from the following ...

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate ...

next page

Showing results 1-20

All JobsDeep Learning JobsRemote Deep Learning JobsRemote Deep Learning Jobs in Missouri

Remote Deep Learning information

See Missouri salary details

$23

$53

$80

How much do remote deep learning jobs pay per hour?

As of Aug 20, 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.

Deep Learning Scientist, Speech Synthesis

Catapult Solutions Group

Saint Louis, MO • On-site, Remote

Contractor

Re-posted 26 days ago

Job description

08/06/26
The hiring manager is looking for people with experience working with autoregressive models, diffusion and flow matching models, FSQ and RVQ codec models, and full-duplex speech-to-speech models.
Deep Learning Scientist - Speech Synthesis
Update on 07/22/26:
No PHD is need just focus on seeking candidates with deep, hands-on expertise in Text-to-Speech (TTS), including experience developing and working with modern SOTA architectures and models. It is essential that their TTS background reflects work with the latest technologies and innovations in speech synthesis, demonstrating current industry knowledge and practical implementation experience.
Update as of 07/21/26: Hi,
We are specifically seeking candidates with deep, hands-on expertise in Text-to-Speech (TTS), including experience developing and working with modern SOTA architectures and models. It is essential that their TTS background reflects work with the latest technologies and innovations in speech synthesis, demonstrating current industry knowledge and practical implementation experience.
Thank you!
Location: 100% Remote (Anywhere in the U.S.)
Duration: 6-Month Contract
Position Overview
We are seeking a Deep Learning Scientist - Speech Synthesis to support the development of next-generation speech AI technologies. This role focuses on training and optimizing speech models, improving model performance, and solving complex machine learning challenges related to speech applications.
The ideal candidate has strong experience in speech synthesis (Text-to-Speech) or Speech-to-Text, deep learning, and Python development. Success in this role requires the ability to analyze model behavior, diagnose training issues, and improve model performance-not just collect or evaluate data.
Key Responsibilities
  • Train and optimize speech synthesis models, including mel spectrogram and vocoder models.
  • Analyze training metrics, validation losses, and model performance to identify root causes of model issues and recommend improvements.
  • Benchmark and optimize speech models across multiple use cases.
  • Improve speech data preparation, augmentation, filtering, and dataset quality.
  • Develop and refine high-quality training datasets for speech AI models.
  • Measure and characterize model accuracy, quality, and bias.
  • Collaborate with cross-functional teams to develop and deliver new speech AI features.
  • Participate in software development, design reviews, testing, and code reviews.
  • Troubleshoot technical issues and contribute to continuous model improvements.
Required Qualifications
  • Master's degree or Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Linguistics, Computational Linguistics, or a related field (or equivalent experience).
  • 3+ years of relevant industry experience.
  • Strong Python programming skills.
  • Strong understanding of machine learning and deep learning concepts.
  • Experience with Text-to-Speech (TTS), Speech Synthesis, or Speech-to-Text (STT) technologies.
  • Hands-on experience training deep learning models using PyTorch.
  • Ability to analyze training behavior, validation losses, and model performance to troubleshoot and improve machine learning models.
  • Knowledge of speech signal processing concepts, including FFT, MFCC, and mel spectrograms.
  • Strong understanding of software development fundamentals.
  • Experience using version control systems such as Git, Gerrit, or GitLab.
  • Excellent communication and collaboration skills.
Preferred Qualifications
  • Experience with deep learning architectures such as CNNs, RNNs, LSTMs, and Transformers.
  • Experience with voice cloning or multilingual speech systems.
  • Knowledge of text normalization (TN), inverse text normalization (ITN), or grapheme-to-phoneme (G2P) systems.
  • Fluency in one or more languages such as Spanish, Mandarin, German, Japanese, Russian, French, Arabic, Hindi, Korean, Italian, or Portuguese.
  • Interest in linguistics, phonetics, and speech technologies.
  • Strong C++ programming skills.
  • Familiarity with GPU technologies such as CUDA, cuDNN, or TensorRT.
  • Experience deploying machine learning models to cloud, data center, or embedded environments.
What We're Looking For
The ideal candidate is someone who enjoys solving difficult machine learning problems and has hands-on experience training speech models. Beyond building models, we're looking for someone who can investigate why a model is underperforming, analyze validation losses, identify root causes, and improve overall model quality and performance.
Additional Information
  • 100% remote position within the United States.
  • No specific U.S. time zone requirement.
  • This is a contract opportunity.
  • Opportunity to contribute to cutting-edge speech AI and deep learning technologies.

Apply