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Machine Learning Intern Remote Jobs in Missouri (NOW HIRING)

Jobgether

Requirements The ideal candidate has a strong academic and practical background in machine learning ... Fully remote, global-first work environment * Opportunity to work on frontier AI research problems ...

Relativity

Principal Applied Scientist

Kansas City, MO · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

Relativity

Principal Applied Scientist

Kansas City, MO · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$89K - $121.50K/yr

Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies ... Experience applying CV and machine learning (ML) techniques to EO imagery and data to address ...

Healthcare Fraud Shield

Data Scientist

Chesterfield, MO · On-site +1

Utilize advanced mathematical models, machine learning algorithms, operations research techniques ... Remote work eligible REMOTE WORK REQUIREMENTS: * Must have high speed Internet (satellite is not ...

Healthcare Fraud Shield

Data Scientist

Chesterfield, MO · On-site +1

Utilize advanced mathematical models, machine learning algorithms, operations research techniques ... Remote work eligible REMOTE WORK REQUIREMENTS: * Must have high speed Internet (satellite is not ...

INFUSE

In-House Counsel (Remote)

Kansas City, MO · Remote

We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our ...

UVeye

Implementation Manager

Kansas City, MO · On-site +1

$80K - $90K/yr

... vision, machine learning, and generative AI within the automotive sector. With over $380M in ... This is a remote role, based on CT or ET. The ideal candidate should be located within an hour of a ...

Jobgether

$88.40K - $106.10K/yr

Familiarity with modern Generative AI frameworks, orchestration tools, and machine learning ... Fully remote work environment offering flexibility and work-life balance. * Personalized career ...

UMB Financial Corporation

AI Data Architect

Kansas City, MO · On-site +1

$62.25 - $80/hr

Currently, we leverage machine learning, natural language processing, predictive analytics, and ... However, the remote location must be within the US. How you will spend your time: * Define and ...

UMB Bank

AI Data Architect

Kansas City, MO · On-site +1

$62.25 - $80/hr

Currently, we leverage machine learning, natural language processing, predictive analytics, and ... However, the remote location must be within the US. How you will spend your time: * Define and ...

UMB Financial

AI Data Architect

Kansas City, MO · On-site +1

$62.25 - $80/hr

Currently, we leverage machine learning, natural language processing, predictive analytics, and ... However, the remote location must be within the US. How you will spend your time: * Define and ...

Jobgether

$88.40K - $106.10K/yr

You will design and build scalable data pipelines that power analytics, machine learning, and real-world scientific and business decisions. Working in a fully remote, international environment, you ...

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Machine Learning Intern Remote information

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

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a remote Machine Learning Intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What does a Machine Learning Intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.

Is ML a high paying job?

Machine Learning (ML) roles are generally considered high-paying within the tech industry due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries for ML positions can vary based on experience, location, and company, but they tend to be above average compared to many other entry-level roles in technology. Internships in ML may offer lower pay, but full-time positions often provide competitive compensation and benefits.
What are the most commonly searched types of Machine Learning Remote jobs in Missouri? The most popular types of Machine Learning Remote jobs in Missouri are:
What are popular job titles related to Machine Learning Intern Remote jobs in Missouri? For Machine Learning Intern Remote jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern Remote jobs in Missouri look for? The top searched job categories for Machine Learning Intern Remote jobs in Missouri are:
Machine Learning Intern Remote jobs near you

AI Research Engineer (Multi-Modal Reinforcement Learning)

Jobgether

Remote

Full-time

Posted 11 days ago

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a AI Research Engineer (Multi-Modal Reinforcement Learning) in Netherlands.

This role sits at the intersection of cutting-edge AI research and large-scale system engineering, focusing on advancing multi-modal reinforcement learning across text, image, audio, and complex simulated environments. You will contribute to the design of next-generation intelligent systems capable of adaptive decision-making in real-world scenarios. Working in a highly research-driven, globally distributed environment, you will help build and scale reinforcement learning frameworks that power advanced multimodal models. Your work will directly influence model performance, training stability, and reward optimization strategies at scale. You will collaborate with top-tier researchers and engineers to push the boundaries of AI capabilities. The role combines deep theoretical research with hands-on system development and experimentation. It is ideal for someone passionate about foundational AI breakthroughs and real-world deployment impact.

Accountabilities

In this role, you will lead research and engineering efforts across multi-modal reinforcement learning systems while contributing to scalable AI infrastructure and experimentation frameworks. You will be responsible for advancing model performance and robustness through innovative algorithm design and rigorous evaluation practices.

  • Conduct research on reinforcement learning methods for multi-modal systems, including diffusion-based and autoregressive model approaches.
  • Design and build scalable RL infrastructure supporting distributed training and evaluation across complex multi-modal environments.
  • Develop reward modeling strategies to improve alignment, training stability, and mitigate failure modes such as reward hacking.
  • Create and curate simulation environments and datasets for training, benchmarking, and validating multi-modal RL models.
  • Design and execute evaluation protocols to measure performance improvements and ensure reproducibility across experiments.
  • Analyze model behavior across modalities, identifying bottlenecks in optimization, exploration, and cross-modal alignment.
  • Explore and develop next-generation RL paradigms to enhance learning from environment feedback and improve SOTA performance.
  • Publish research in leading AI conferences such as NeurIPS, ICML, ICLR, CVPR, and related venues.
Requirements

The ideal candidate has a strong academic and practical background in machine learning, reinforcement learning, and multi-modal AI systems, with a proven record of research excellence and scalable system development. You are comfortable working at the frontier of AI research while building production-grade experimentation pipelines.

  • Master's degree in Computer Science or related field required; PhD preferred in ML, CV, NLP, or AI-related disciplines.
  • Strong publication record in top-tier AI conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV).
  • Proven experience in large-scale reinforcement learning experiments, particularly in multi-modal or vision-centric systems.
  • Deep understanding of reinforcement learning theory, optimization, and policy learning in high-dimensional environments.
  • Strong hands-on experience with PyTorch and deep learning frameworks for multimodal AI systems.
  • Experience building end-to-end RL pipelines including simulation, training, evaluation, and deployment.
  • Ability to address core RL challenges such as sample efficiency, exploration-exploitation trade-offs, and training stability.
  • Strong analytical and problem-solving skills with a research-driven, experimental mindset.
Benefits
  • Competitive compensation package aligned with top-tier AI research talent
  • Fully remote, global-first work environment
  • Opportunity to work on frontier AI research problems at scale
  • High-impact role influencing next-generation multimodal intelligence systems
  • Collaboration with leading researchers and engineers in AI and reinforcement learning
  • Access to large-scale experimentation infrastructure and research resources
  • Strong culture of innovation, autonomy, and research publication support
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. 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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