ZipRecruiter

Log In

2

Remote Ai Engineer Jobs in Missouri (NOW HIRING)

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

Sr AI Engineer / Data Scientist / MLOps Consultant Location ... United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and ...

Jobgether

As a Staff AI Engineer, you'll serve as a senior technical leader responsible for shaping the ... Fully remote working environment with the flexibility to work from anywhere. * One-time home office ...

Jobgether

$100K - $120K/yr

Our partner is looking for an AI/ML & Forward Deployed Engineer based in Netherlands. This role ... Competitive annual salary of $100,000-$120,000 . * Full-time opportunity with a remote working ...

Jobgether

$80K - $110K/yr

Our partner is looking for a Senior AI/ML Engineer based in Netherlands. This is a senior-level ... You will work in a remote environment where strong communication, problem-solving, and ownership ...

Jobgether

Our partner is looking for a MarTech Engineer - AI & Automation based in Netherlands. This is a ... Fully remote, remote-first working environment. * Flexible working arrangements across Europe.

next page

Showing results 1-20

All JobsAi Engineer JobsRemote Ai Engineer JobsRemote Ai Engineer Jobs in Missouri

Remote Ai Engineer information

See Missouri salary details

$23

$50

$71

How much do remote ai engineer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for remote ai engineer in Missouri is $50.31, according to ZipRecruiter salary data. Most workers in this role earn between $40.58 and $58.41 per hour, depending on experience, location, and employer.

What is a remote AI engineer?

A Remote AI Engineer is a professional who designs, develops, and deploys artificial intelligence models and systems while working from a remote location. They use machine learning, deep learning, and data science techniques to build AI-powered applications, improve automation, and solve complex problems. Responsibilities often include data preprocessing, model training, fine-tuning, and integrating AI solutions into products or services. These engineers collaborate with cross-functional teams online, using cloud-based tools and platforms for development and deployment. Remote AI Engineers typically need strong programming skills in languages like Python, experience with frameworks like TensorFlow or PyTorch, and familiarity with cloud computing and MLOps.

What is it like collaborating with team members as a remote AI engineer?

As a Remote AI Engineer, collaboration typically occurs through virtual meetings, code reviews, shared documentation, and messaging platforms like Slack or Teams. You will work closely with data scientists, product managers, and software engineers to define requirements, design solutions, and integrate AI models into products or services. Strong communication and proactive reporting are highly valued to ensure project alignment and seamless progress. Effective collaboration in a remote setting not only enhances project outcomes but also fosters professional growth and a sense of team cohesion.

What are the most commonly searched types of Ai Engineer jobs in Missouri?

The most popular types of Ai Engineer jobs in Missouri are:

What are popular job titles related to Remote Ai Engineer jobs in Missouri?

For Remote Ai Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Ai Engineer jobs in Missouri look for?

The top searched job categories for Remote Ai Engineer jobs in Missouri are:

What cities in Missouri are hiring for Remote Ai Engineer jobs?

Cities in Missouri with the most Remote Ai Engineer job openings:

Remote Ai Engineer jobs near you
Infographic showing various Remote Ai Engineer job openings in Missouri as of August 2026, with employment types broken down into 2% Internship, 79% Full Time, and 19% Contract. Highlights an 100% Remote job distribution, with an average salary of $104,636 per year, or $50.3 per hour.

Senior AI Engineer

Koantek

Chesterfield, MO • Remote

$54.75 - $70.50/hr

Contractor

Re-posted 4 days ago

Key responsibilities

  • Lead and execute end-to-end ML project implementations directly with clients, translating business problems into technical solutions.

  • Design, build, and maintain production-grade ML pipelines with a focus on CI/CD and MLOps practices to ensure model reliability and scalability.

  • Implement and optimize Generative AI and NLP applications, including technologies like RAG and LLMs, in a production environment.

Job description

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. 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 will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions

Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences. Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models. Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.

Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems. Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark). Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities

Ensure all client engagements and training activities are properly documented and reported via designated partner platforms. Required Qualifications 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment. 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

Excellent verbal and written communication skills for effective client and internal team interaction. Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices. Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

Deep understanding of programming for data-intensive and scalable ML applications. Proven experience in deploying and managing Generative AI and NLP solutions for client applications. Preferred Qualifications Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures. Requirements Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

Apply