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Artificial Intelligence Machine Learning Engineer Jobs in Missouri

Deloitte

AI Solutions Architect

Kansas City, MO · On-site

$61.50 - $81/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

AI Solutions Architect

Saint Louis, MO · On-site

$61.25 - $80.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

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All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Missouri

Artificial Intelligence Machine Learning Engineer information

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$29.5K

$120.8K

$181.5K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for artificial intelligence machine learning engineer in Missouri is $120,786.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $145,400.00 per year, depending on experience, location, and employer.

What is an Artificial Intelligence Machine Learning Engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by Artificial Intelligence Machine Learning Engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Missouri? For Artificial Intelligence Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Missouri look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Missouri are:
What cities in Missouri are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities in Missouri with the most Artificial Intelligence Machine Learning Engineer job openings:
Artificial Intelligence Machine Learning Engineer jobs near you
Machine Learning Engineer with Security Clearance

Machine Learning Engineer with Security Clearance

SecureVision

Saint Louis, MO • On-site

Other

Posted 3 days ago

Job description

HOW A MACHINE LEARNING ENGINEER WILL MAKE AN IMPACT
Own your opportunity to serve as a critical component of our nation's safety and security. Make an impact by using your expertise to protect our country from threats. Job Description
Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions. You will be at the cutting edge of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) for conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets such as satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap.
WHAT YOU'LL NEED TO SUCCEED:
• Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
• Experience: 5+ years Technical skills:
• Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models to quickly perform segmentation and object detection tasks with limited training data using satellite imagery.
• Demonstrated professional or academic experience building secure containerized Python applications to include hardening, scanning, automating builds using CI/CD pipelines.
• Demonstrated professional or academic experience using Python to query and retrieve imagery from S3 compliant API's perform common image preprocessing such as chipping, augment, or conversion using common libraries like Boto3 and NumPy.
• Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
• Demonstrated professional or academic experience with version control systems such as Gitlab.
• Demonstrated experience leveraging CUDA for GPU accelerated computing. Skills and abilities desired:
• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
• Demonstrated experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
• Demonstrated experience with Vision Transformers (ViT) such as DINO or DeiT.
• Demonstrated academic or professional experience communicating methodological choices and model results.
• Demonstrated experience with verification and validation test benches.
• Demonstrated experience with Explainable AI (XAI) techniques.
• Demonstrated experience with Open Neural Net Exchange (ONNX).

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