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Mlops Manager Jobs in Indiana (NOW HIRING)

... management, and striving for outcomes. This goal extends to how we hire and onboard our most ... As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production ...

... management, and striving for outcomes. This goal extends to how we hire and onboard our most ... As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production ...

Our end-to-end suite of software solutions helps customers manage emergency communications, process ... End-to-End MLOps and Deployment: Own the entire engineering lifecycle for central, reusable ...

Data Systems/Solutions Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

DataOps / MLOps Enablement: * Implement CI/CD practices for data and ML workflows, including ... Ensure appropriate handling of sensitive data through de-identification, access management, and ...

... risk management of advanced analytics, machine learning, and AI models deployed in federal ... You will work closely with data scientists, MLOps engineers, system owners, risk stakeholders, and ...

... risk management of advanced analytics, machine learning, and AI models deployed in federal ... You will work closely with data scientists, MLOps engineers, system owners, risk stakeholders, and ...

Data Architect

Indianapolis, IN

$61 - $78.25/hr

Familiarity with MLOps and how data architecture supports model lifecycle management * Knowledge of data cataloging, semantic layers, and enterprise metadata strategies * Experience designing data ...

Data Architect

Indianapolis, IN · On-site

$61 - $78.50/hr

Familiarity with MLOps and how data architecture supports model lifecycle management * Knowledge of data cataloging, semantic layers, and enterprise metadata strategies * Experience designing data ...

... management, MLOps, and cloud-native deployments. • Strong expertise with platforms such as Azure Machine Learning, AWS SageMaker, Google Vertex AI, Databricks, and OpenAI APIs. • Demonstrated ...

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ... Non-Management Exempt Workshift: 1st Shift (United States of America) Job Family: IFT > Artificial ...

Work closely with the MLOps team to create and maintain robust evaluation solutions and tools to ... Excellent written & verbal communication and stakeholder management skills. * 4+ years project ...

Senior AI/ML Engineer

Bedford, IN · On-site

$93K - $128K/yr

Partner with project managers and engineering teams to define objectives for AI/ML systems in ... Demonstrated experience with LLMs, MLOps pipelines, and modern ML frameworks (e.g., PyTorch ...

... management, short-term and long-term memory, tool-calling orchestration, and the ability to ... MLOps platform, experiment tracking, model versioning, automated evaluation, deployment pipelines ...

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Mlops Manager information

What engineer makes $500,000 a year?

Senior machine learning engineers and MLOps managers with extensive experience, advanced skills in cloud platforms, and expertise in deploying scalable AI systems can earn $500,000 or more annually. High compensation often reflects leadership roles, specialized knowledge, and working in high-demand industries or companies with competitive benefits.

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.

What are the key skills and qualifications needed to thrive as an MLOps Manager, and why are they important?

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as an AI executive, senior machine learning engineer, or AI research director, often requiring advanced skills, extensive experience, and leadership responsibilities. These roles may involve overseeing AI strategy, developing complex models, and managing teams, with compensation reflecting the seniority and impact of the position.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and their role is unlikely to be fully replaced by AI. Instead, AI tools can augment their work by automating routine tasks, allowing MLEs to focus on complex problem-solving, model optimization, and system integration. Continuous learning and expertise in AI frameworks and programming are essential for MLEs to stay relevant in evolving technological 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.

Is MLOps in high demand?

MLOps managers are in high demand due to the increasing adoption of machine learning and AI across industries. Organizations seek professionals skilled in deploying, monitoring, and maintaining ML models using tools like Kubernetes, Docker, and cloud platforms, making MLOps a rapidly growing field with strong job prospects.

What are MLOps Managers?

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 most commonly searched types of Mlops jobs in Indiana? The most popular types of Mlops jobs in Indiana are:
What cities in Indiana are hiring for Mlops Manager jobs? Cities in Indiana with the most Mlops Manager job openings:

MLOps Automation Senior Lead Engineer

Huntington

Indianapolis, IN • On-site, Remote

$99K - $130K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 4 days ago


Job description

Description

Summary:

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and deploying MLOps Automation for some of Huntington's most valuable and most challenging data-driven projects.

Duties and Responsibilities:

  • Streamline the data, analytics, and model development lifecycle by identifying pain points and productivity barriers and determining ways to resolve them through automation.
  • Helps set the strategy and tone for MLOps Automating Engineering strategy and vision for the future.
  • Understand the current process and technical complexities of developing and deploying data pipelines and model builds and develop automation solutions to improve and extend the existing process to become an unattended delivery pipeline.
  • Collaborate closely with product development, architecture, data engineering and testing teams to understand their current build and release processes and make recommendations for improvement through the automation of various tasks.
  • Partner with cross-functional stakeholders, including development, operations, quality assurance and security, to streamline processes.
  • Develop and continuously improve automation solutions to enable teams to build and deploy quality data and code efficiently and consistently.
  • Build automated testing solutions in support of quality management objectives to reduce manual effort.
  • Build automated environment provisioning solutions in response to changes in processing demand.
  • Build automated feedback mechanisms to monitor the performance of models in production.
  • Work closely with cross-functional stakeholders to analyze and troubleshoot complex production issues.
  • Prepare and present design and implementation documentation to multiple stakeholders.
  • Promote automation across the data management and analytics delivery organization.
  • Perform other duties as assigned.

Basic Qualifications:

  • Bachelor's Degree (Computer Science, Business Administration, Economics or related fields) or equivalent relevant work experience
  • 10+ years of relevant automation engineering experience, of software engineering, in strategy, management consulting, or similar skillset, and of technical leadership experience with data-centric products
  • 10+ years of experience with one or more coding languages (e.g., JavaScript, C++, Python, Java), CI/CD tools (e.g., Jenkins, Artifactory, CircleCI, Ansible), and development platforms (e.g., AWS, Azure, Docker, Kubernetes)

Preferred Qualifications:

  • Strong collaboration skills, with a demonstrated ability to work well as part of a team
  • Experience developing CI/CD workflows and tools
  • Strong automation scripting skills
  • Experience in configuration management, test-driven development, and release management.
  • Strong analytical and troubleshooting skills.
  • Experience with agile development and strong understanding of DataOps and ModelOps principles
  • Ability to investigate and analyze information, and to draw conclusions
  • Flexibility, adaptability, and desire to learn new languages and technologies
  • Strong verbal and written communication skills
  • Demonstrated ability to work independently across multiple tasks while meeting aggressive timelines
  • Strategic, intellectually curious thinker with focus on outcomes
  • Professional image with the ability to form relationships across functions
  • Ability to train more junior analysts regarding day-to-day activities, as necessary
  • Proven ability to lead cross-functional efforts
  • Willingness and ability to learn new technologies on the job
  • Financial Services background


Exempt Status: (Yes= not eligible for overtime pay) (No= eligible for overtime pay)

Yes

Workplace Type:

Office

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Compensation Range:

Total Base Pay Range 93,000.00 - 189,000.00 USD Annual

The compensation range represents the anticipated low and high end of the base compensation range for this position. Actual compensation will vary based on various factors including but not limited to location, experience, and education. Colleagues in this position are also eligible to participate in an applicable incentive compensation plan. In addition, Huntington provides a variety of benefits to colleagues, including health insurance coverage, wellness program, life and disability insurance, retirement savings plan, paid leave programs, paid holidays and paid time off (PTO).

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters: Huntington will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington colleagues, directly or indirectly, will be considered Huntington property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.