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Mlops Manager Jobs in Kansas (NOW HIRING)

Resources of Kenya

Project Manager

Kansas City, KS · On-site

In terms of skills, they are looking for experts in risk adjustment coding, MLOps engineering ... Manage changes to the project scope, project schedule, and project costs using appropriate ...

Guida's Dairy

AI Enterprise Architect

Kansas City, KS · On-site

$66.50 - $85.75/hr

Experience with MLOps and governance frameworks preferred * Deep expertise in AI/ML and GenAI architectures, including model deployment, integration, and lifecycle management * Strong command of ...

Dairiconcepts, L.P.

AI Enterprise Architect

Kansas City, KS · On-site

$66.50 - $85.75/hr

Experience with MLOps and governance frameworks preferred * Deep expertise in AI/ML and GenAI architectures, including model deployment, integration, and lifecycle management * Strong command of ...

Reply

Manager, Data Engineering

Kansas City, KS · On-site

At Valorem Reply, we are hiring a Manager for the Data & AI team. The person will mainly focus on ... MLOps * Knowledge and familiarity with Microsoft Purview * DevOps for data, GitHub, automated ...

Kforce Technology Staffing

AI Architect

Wichita, KS · On-site

$62.25 - $82/hr

Experience operationalizing AI - LLMOps/MLOps practices for model deployment, evaluation, prompt and version management, monitoring, and drift detection * Experience with vector databases and ...

CrowdStrike

Establish best practices for MLOps/DataOps surrounding LLMs, including monitoring, observability ... Collaborate across the organization with Data Scientists, Product Managers, and other engineering ...

Deloitte

AI Security Engineer Manager

Wichita, KS

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... MLOps pipelines. Communication and Influence Clearly articulate technical risks, trade-offs, and ...

Guida's Dairy

Sr. Systems Engineer - AI

Kansas City, KS · On-site

$100K - $137K/yr

Manage the full operational lifecycle of AI-enabled services, including versioning and controlled ... MLOps), AI-enabled applications, large-scale data platforms, or other advanced analytics ...

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Mlops Manager information

What is an MLOps manager?

MLOps Managers are professionals responsible for overseeing the deployment, operation, and scaling of machine learning models in production environments. They coordinate teams to ensure seamless collaboration between data scientists, engineers, and IT staff, facilitating the automation of machine learning workflows. Their role involves managing infrastructure, optimizing processes for model monitoring and maintenance, and ensuring compliance with organizational and industry standards. MLOps Managers play a key role in bridging the gap between model development and operationalization, ensuring that machine learning solutions are reliable, reproducible, and scalable.

What are the key skills and qualifications needed to thrive as an MLOps manager?

To thrive as an MLOps Manager, you need expertise in machine learning, software engineering, and DevOps practices, often backed by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, Azure, GCP), and certifications such as AWS Certified Machine Learning or Google Cloud Professional ML Engineer are highly beneficial. Strong leadership, problem-solving, and cross-functional communication skills help manage teams and bridge the gap between data science and IT operations. These abilities are crucial for ensuring reliable, scalable, and efficient deployment of machine learning solutions in production environments.

What are some common challenges an MLOps manager faces when integrating machine learning models into production environments?

MLOps Managers often encounter challenges such as ensuring seamless collaboration between data science and engineering teams, managing model versioning, and maintaining reliable deployment pipelines. Balancing rapid experimentation with the need for robust, scalable, and secure production systems can be complex. Additionally, monitoring model performance post-deployment and handling data drift or model degradation are ongoing responsibilities. Effective communication and establishing standardized processes are key to overcoming these challenges and ensuring successful model operations.

What is the difference between Mlops Manager vs Data Scientist?

AspectMlops ManagerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; certifications in cloud platforms or MLOps toolsBachelor's/Master's in CS, Statistics, or related; certifications in data analysis or machine learning
Work EnvironmentCollaborates with engineering, DevOps, and data teams to deploy and maintain ML systemsAnalyzes data, builds models, and provides insights to inform business decisions
Employer & Industry UsageTech companies, AI startups, enterprises implementing ML pipelinesResearch institutions, tech firms, finance, healthcare, and marketing sectors

The Mlops Manager focuses on deploying, maintaining, and optimizing machine learning systems within an organization, working closely with engineering and DevOps teams. In contrast, a Data Scientist primarily analyzes data, develops models, and provides insights. While both roles require knowledge of machine learning, the Mlops Manager emphasizes operationalizing ML solutions, whereas the Data Scientist emphasizes data analysis and modeling.

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Mlops Manager jobs near you

Project Manager

Resources of Kenya

Kansas City, KS • On-site

Contractor

Re-posted 22 days ago

Job description

Company Description

Our client is an international Healthcare AI company that specializes in providing AI-powered risk adjustment solutions and services to healthcare providers and payers. They are seeking for individuals who are driven by curiosity, inspired by challenges, and motivated to make a difference. They value work-life balance, flexible hours, and a supportive culture. In terms of skills, they are looking for experts in risk adjustment coding, MLOps engineering, solution architecture, research engineering, and DevOps engineering.

Job Description
  • Define project scope, goals, and deliverables that support business goals in collaboration with senior management and stakeholders.
  • Develop detailed project plans, schedules, and budgets.
  • Coordinate internal resources and third parties/vendors for the flawless execution of projects.
  • Ensure resource availability and allocation across tasks and phases.
  • Track project performance using appropriate tools and techniques.
  • Manage changes to the project scope, project schedule, and project costs using appropriate verification techniques.
  • Measure project performance to identify areas for improvement.
  • Report and escalate issues to management as needed.
  • Create and maintain comprehensive project documentation.
  • Foster strong working relationships with clients and team members.
Qualifications
  • Prior experience in data collection or AI/ML-related field projects
  • Strong on-ground execution skills including scheduling, participant coordination, and stakeholder communication
  • Ability to manage multi-location shoot logistics, ensure quality control, and maintain compliance with data privacy and safety regulations (HIPAA, FERPA, etc.)
  •  Project Management Professional (PMP) certification is a plus.
  •  Excellent written and verbal communication skills.
Additional Information

All your information will be kept confidential according to EEO guidelines.

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