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Software Engineer Ai Model Training Jobs in Missouri

Jobtailor

Software Engineer, ML Infrastructure

California, MO · On-site

$154K - $183K/yr

... AI model serving * Build infrastructure to perform scalable ML model training, evaluation, and ... Work closely with ML engineers to deploy cutting‑edge models into production * Utilize AI tools ...

Jobtailor

Staff AI Software Engineer

California, MO · On-site

Experience with AI models and algorithms, including LLMs, DNN, genetic algorithms, embedding models ... Understanding of software engineering best practices, including source control and software ...

MasterCard

Senior AI Platform Engineer (DevOps)

O Fallon, MO · On-site

$121K - $156K/yr

Develop and maintain infrastructure, tooling, and services that support model training, evaluation ... Strong software engineering and automation experience using Python. Experience implementing CI/CD ...

Epiq

AI Software Engineer

Kansas City, MO · Remote

Epiq is seeking a highly skilled AI Software Engineer to join our Operations Engineering team. This ... Hands-on experience with GenAI, model training, evaluation, and hyperparameter tuning. * Experience ...

Jobgether

Our partner is looking for a AI Researcher - Training Optimization based in Netherlands. This ... model quality. * Close collaboration with infrastructure and inference engineering teams.

MasterCard

Senior Software Engineer

O Fallon, MO · On-site

$114K - $151K/yr

Title and Summary Senior Software Engineer Who is Mastercard? Mastercard is a global technology ... model training, tuning, and inference workflows Implement and operate AI systems in production ...

Jobtailor

Staff AI Engineer

California, MO · On-site

... engineers, research scientists, technical program managers, and product managers to deliver AI ... software components, including foundation model training, LLM inference, similarity search ...

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Software Engineer Ai Model Training information

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What are popular job titles related to Software Engineer Ai Model Training jobs in Missouri?

For Software Engineer Ai Model Training jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Software Engineer Ai Model Training jobs in Missouri look for?

The top searched job categories for Software Engineer Ai Model Training jobs in Missouri are:

What cities in Missouri are hiring for Software Engineer Ai Model Training jobs?

Cities in Missouri with the most Software Engineer Ai Model Training job openings:

Software Engineer Ai Model Training jobs near you
Infographic showing various Software Engineer Ai Model Training job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, and 4% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Software Engineer, ML Infrastructure

California, MO • On-site

Jobtailor
See more jobs at Jobtailorexternal

$154K - $183K/yr

Other

Posted 24 days ago

Job description

Responsibilities
  • Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
  • Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
  • Develop high-performance inference systems to ensure fast and efficient AI model serving
  • Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
  • Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
  • Work closely with ML engineers to deploy cutting‑edge models into production
  • Utilize AI tools and high-velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production‑ready quality code
Requirements
  • Bachelor’s degree in a technical field such as computer science or equivalent experience
  • 2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ year of post‑grad software development experience; or PhD in a relevant technical field
  • Experience building large‑scale production machine learning systems, distributed systems or big data processing
  • Strong programming skills in Python, Java, Scala or C++
  • Strong problem‑solving skills with a focus on system performance, scalability, and efficiency
  • Good understanding of distributed systems and the infrastructure components of large‑scale ML
  • Experience with big data processing frameworks such as Spark, Flink, or Ray
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