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Remote Deep Learning Jobs in Missouri (NOW HIRING)

Jobgether

If you're passionate about LLMs, deep learning, and delivering scalable machine learning solutions ... Benefits * Fully remote work environment with collaboration across an international team.

Jobgether

This is an opportunity for an ML engineer who enjoys deep technical challenges, experimentation ... Remote-friendly work environment with an async-first culture. * Opportunity to solve challenging AI ...

Jobgether

$88K - $106K/yr

You will dive deep into performance optimization, from model architecture and GPU execution to ... Flexible remote work environment. * Opportunity to contribute to the growth of an innovative AI ...

Jobgether

$76K - $96K/yr

Deep knowledge and hands-on experience in areas such as model-based reinforcement learning, model ... Ability to collaborate effectively in a remote, international environment while demonstrating ...

New

Jobgether

The position requires a visionary technical leader who can combine deep machine learning expertise ... Fully remote working environment with flexibility to work from different regions worldwide.

Jobgether

Deep understanding of machine learning infrastructure, distributed training, and GPU-based ... Remote-first working environment with flexibility across eligible locations. * Opportunity to work ...

Jobgether

$76K - $96K/yr

Deep expertise in evaluating model performance, understanding failure modes, and making informed ... Fully remote position with the flexibility to work from Europe. * Opportunity to influence the ...

New

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 ...

Kemper

Senior Data Engineer

Saint Louis, MO · Remote

$103K - $140K/yr

... PA, Remote-RI, Remote-VA, St. Louis, Missouri Details Kemper is one of the nation's leading ... This role requires deep technicalexpertisewith Snowflake,Core AWS Services, cloud-based ...

Third-Party Job Posts

Location - Remote (Europe) How You'll Make an Impact: As a Staff Machine Learning Engineer , you ... Deep MLOps Proficiency: Expert-level knowledge of CI/CD, orchestration (e.g., Apache Airflow, Flink ...

Jobgether

$80K - $110K/yr

You will work at the intersection of machine learning engineering, MLOps, and research, enabling ... Develop a deep understanding of internal platforms, tools, and technical capabilities to support ...

New

Jobgether

... machine learning venues such as NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, or arXiv. * Deep ... Fully remote position offering flexibility and autonomy. * Competitive compensation package with ...

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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 Jul 31, 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 job?

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 are some 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.

How can I make $100,000 a year working from home?

A remote deep learning professional can reach a $100,000 annual income by gaining advanced skills in machine learning frameworks, building a strong portfolio, and working for companies that offer competitive salaries or freelance projects. Earning this level often requires experience, specialized knowledge, and the ability to deliver high-quality models efficiently. Certifications in deep learning and proficiency with tools like Python, TensorFlow, or PyTorch can also enhance earning potential.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

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.

Which 3 jobs will survive AI?

In the field of remote deep learning, roles such as data scientists, machine learning engineers, and AI research scientists are likely to persist due to their reliance on complex problem-solving, domain expertise, and ongoing innovation. These jobs require advanced skills in programming, mathematics, and understanding of AI frameworks, making them less susceptible to automation by AI systems. Continuous learning and staying updated with new tools and techniques are essential for long-term career stability in this area.

How to make $1000 a week remotely?

Remote deep learning professionals can earn $1000 or more weekly by taking on freelance projects, consulting, or working for companies that pay competitive rates. Building a strong portfolio, acquiring relevant skills in Python and machine learning frameworks, and obtaining certifications can help increase earning potential. Consistent work and specialized expertise are key to reaching this income level remotely.

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

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 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 July 2026, with employment types broken down into 72% Full Time, 25% Part Time, and 3% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $110,433 per year, or $53.1 per hour.

Machine Learning Engineer - Large Language Models

Jobgether

On-site, Remote

Full-time

Medical, Life

Posted 4 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer - Large Language Models based in Netherlands.

Join a highly collaborative and innovation-driven environment where you'll help shape the future of AI-powered healthcare solutions. In this role, you'll design, optimize, and deploy advanced Large Language Models that support real-world applications across healthcare and life sciences. Working alongside multidisciplinary experts in machine learning, software engineering, and scientific domains, you'll contribute to cutting-edge AI initiatives with meaningful impact. This is an opportunity to solve complex technical challenges, leverage state-of-the-art technologies, and influence the development of production-ready AI systems. If you're passionate about LLMs, deep learning, and delivering scalable machine learning solutions, this role offers an exciting platform to grow your expertise while contributing to transformative projects.

Accountabilities
  • Fine-tune and optimize Large Language Models for a variety of healthcare and life science applications using techniques such as Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (PEFT), Direct Preference Optimization (DPO), and Proximal Policy Optimization (PPO).
  • Develop and enhance Retrieval-Augmented Generation (RAG) pipelines to improve the accuracy, relevance, and efficiency of AI-powered information retrieval systems.
  • Collect, prepare, clean, and curate high-quality datasets to support the training, evaluation, and continuous improvement of machine learning models.
  • Convert, optimize, and package AI models for production deployment across different serving environments while ensuring scalability and performance.
  • Collaborate with cross-functional teams to build, evaluate, and deploy robust deep learning solutions that address complex healthcare challenges.
  • Stay up to date with emerging advancements in LLMs, machine learning infrastructure, and AI engineering best practices to continuously improve model performance and reliability.
Requirements
  • At least 5 years of professional experience developing production-grade software engineering and deep learning solutions.
  • Degree in Computer Science, Data Science, Machine Learning, or a related technical field; a Master's or Ph.D. is strongly preferred.
  • Proven experience working with Large Language Models, including model fine-tuning and optimization techniques.
  • Hands-on expertise with frameworks such as Axolotl and strong knowledge of Transformer-based architectures.
  • Experience with machine learning frameworks, particularly PyTorch.
  • Familiarity with model serving technologies such as vLLM, Text Generation Inference (TGI), and llama.cpp.
  • Understanding of model quantization techniques and performance optimization for resource-constrained environments.
  • Strong problem-solving, collaboration, and communication skills with the ability to work effectively in distributed teams.
  • Passion for AI innovation and applying machine learning to impactful real-world use cases.
Benefits
  • Fully remote work environment with collaboration across an international team.
  • Competitive compensation package.
  • Opportunity to work on cutting-edge AI and Large Language Model technologies.
  • Continuous learning and professional development opportunities.
  • Exposure to impactful projects within healthcare, life sciences, and open-source AI.
  • Inclusive, diverse, and collaborative workplace committed to equal opportunity and fair hiring practices.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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