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Ml Infrastructure Jobs in Kansas (NOW HIRING)

... infrastructure and services such as Azure cloud platforms and On- premise environments Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data environments (such as Splunk ...

Senior Cloud Engineer

Wichita, KS · On-site

$49.75 - $66.75/hr

Exposure to FinOps, disaster recovery planning, cloud security tooling, policy-as-code, or AI/ML infrastructure needs. At Koch companies, we are entrepreneurs. This means we openly challenge the ...

Senior Cloud Engineer

Wichita, KS · On-site

$120 - $180/hr

Exposure to FinOps, disaster recovery planning, cloud security tooling, policy-as-code, or AI/ML infrastructure needs. At Koch companies, we are entrepreneurs. This means we openly challenge the ...

Sr. Systems Engineer - AI

Kansas City, KS · On-site

$100K - $137K/yr

This role ensures that AI/ML capabilities are delivered into production environments using the same operational rigor, reliability standards, and support models as enterprise IT infrastructure ...

Sr. Systems Engineer - AI

Kansas City, KS · On-site

$100K - $137K/yr

This role ensures that AI/ML capabilities are delivered into production environments using the same operational rigor, reliability standards, and support models as enterprise IT infrastructure ...

Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible. * Experience with Kubernetes and Python programming. * Solid understanding of GPU computing, including ML training ...

Sr. Data Engineer - AI

Kansas City, KS

$110K - $132K/yr

... AI/ML models. Ensure data is accurate, current, compliant, and aligned with enterprise AI ... Own key AI data infrastructure components and ensure they are scalable, maintainable, and supported ...

Sr. Data Engineer - AI

Kansas City, KS · On-site

$110K - $132K/yr

... AI/ML models. Ensure data is accurate, current, compliant, and aligned with enterprise AI ... Own key AI data infrastructure components and ensure they are scalable, maintainable, and supported ...

$195K - $286K/yr

You will partner closely with ML Platform, Infrastructure, Onboard Autonomy, and Simulation teams to deliver compressed models that meet the performance requirements of both real-time onboard systems ...

$89K - $123K/yr

About the Role We are seeking an experienced Senior ML Inference Engineer to join our team ... inference infrastructure meets FDA and SOC2 compliance requirements. This role offers the ...

Senior AWS Cloud Architect

Park City, KS · On-site

$58 - $76/hr

Ensure the underlying infrastructure optimized for high-performance data analytics, reporting pipelines, and advanced AI/ML modeling. • Cost Optimization & Performance Tuning: Implement FinOps ...

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Ml Infrastructure information

What is ML infrastructure?

ML Infrastructure refers to the underlying systems, tools, and processes that enable the development, deployment, and scaling of machine learning models. This includes data storage and management, computing resources, model training and serving environments, monitoring, and automation tools. ML Infrastructure ensures that data scientists and engineers can efficiently build, test, and maintain machine learning applications in a reliable and reproducible manner. It is a crucial foundation for organizations looking to operationalize AI and machine learning solutions at scale.

What are some common challenges faced by professionals working in ML infrastructure roles?

Professionals in ML Infrastructure often encounter challenges related to scaling systems to handle large volumes of data, ensuring reliable deployment pipelines, and maintaining reproducibility across different environments. They must also collaborate closely with data scientists and engineers to streamline workflows and address issues like version control and model monitoring. Staying updated with rapidly evolving tools and best practices is essential, and balancing stability with innovation is a frequent aspect of the role.

What are the key skills and qualifications needed to thrive as an ML infrastructure engineer, and why are they important?

To thrive as an ML Infrastructure Engineer, you need a strong background in software engineering, cloud computing, and machine learning concepts, often supported by a degree in computer science or a related field. Proficiency with containerization tools (like Docker and Kubernetes), cloud platforms (such as AWS, GCP, or Azure), and CI/CD systems is critical. Excellent problem-solving, collaboration, and communication skills help you efficiently work with data scientists and DevOps teams. These skills and qualities are vital for building scalable, reliable ML systems that support rapid experimentation and deployment in production environments.

What is the difference between Ml Infrastructure vs Data Engineer?

AspectML InfrastructureData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of cloud platformsBachelor's in CS, Software Engineering, or related; experience with databases and ETL tools
Work EnvironmentFocus on deploying and maintaining ML systems, cloud environments, and infrastructure toolsDesigning, building, and managing data pipelines and storage solutions
Industry UsageUsed in AI/ML teams to support model deployment and scalabilityUsed across data-driven organizations for data management and analytics

ML Infrastructure specialists focus on deploying, scaling, and maintaining machine learning systems and infrastructure, while Data Engineers primarily build and manage data pipelines and storage solutions. Both roles require technical skills and often collaborate, but their core responsibilities differ in focus and tools used.

What are popular job titles related to Ml Infrastructure jobs in Kansas?

For Ml Infrastructure jobs in Kansas, the most frequently searched job titles are:

What job categories do people searching Ml Infrastructure jobs in Kansas look for?

The top searched job categories for Ml Infrastructure jobs in Kansas are:

Infographic showing various Ml Infrastructure job openings in Kansas as of August 2026, with employment types broken down into 89% Full Time, 8% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Data Scientist / ML Engineer

Overland Park, KS • On-site

Highbrow LLC
IT Services • 11 - 50 employees

$100 - $130/hr

Other

Posted 22 days ago


Job description

Data Scientist / ML Engineer

Year Of Experience: 7+ years

Location: Overland Park KS/ Frisco TX ( 5 days onsite from day 1)

Visa Type :- (US Citizen only ) (Female candidate only required )

Employment Type :- W2

Duration :- Long Term

Job Description :-

7plus years of experience in statistical modeling, data mining, analytics techniques, machine learning software development and reporting

3plus years of applied experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect their performance.

3plus years of hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.

3 plus years of experience in building use cases / solutions especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure cloud platforms and On- premise environments

Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.)

Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations.

Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.

Expertise with scaling pilot machine learning solutions to a large scale production environment

Expertise with visualization tools such as PowerBI, D3JS etc.

Excellent written and verbal communication skills.

Proficient in machine learning data workflows, data collection methodologies, and data analysis.

Experience with architecting, designing, developing software solution in Azure and on-prem

environments.

Certifications AI / ML and Azure Cloud platforms will be plus

Education:

  • Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
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