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Mlops Engineer Jobs in Indiana (NOW HIRING)

RR

Data Systems/Solutions Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

The Engineer applies modern software engineering and data engineering practices to ensure data ... DataOps / MLOps Enablement: * Implement CI/CD practices for data and ML workflows, including ...

Guidehouse

Model Validation Lead

Indianapolis, IN

You will work closely with data scientists, MLOps engineers, system owners, risk stakeholders, and government counterparts to define validation standards, execute reviews, and ensure alignment with ...

Group1001

Staff ML Engineer

Zionsville, IN

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape ...

Group1001

Staff ML Engineer

Zionsville, IN

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape ...

INFOSYS NOVA HOLDINGS LLC

Lead Engineer

Indianapolis, IN · On-site

$97K - $129K/yr

The engineer will operate at the intersection of distributed systems engineering, applied machine learning infrastructure, AI security, and MLOps, translating experimental NLP and generative AI ...

Vergence

Senior AI/ML Engineer

Bedford, IN · On-site

$93K - $128K/yr

Demonstrated experience with LLMs, MLOps pipelines, and modern ML frameworks (e.g., PyTorch, TensorFlow). * Strong background in software and cyber engineering principles, including system hardening ...

Deloitte

AI Engineer Senior Consultant

Indianapolis, IN · Hybrid

$99K - $137K/yr

AI Engineer Senior Consultant Our Deloitte Human Capital team transforms technology platforms ... Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated ...

Performacentric

ML Engineer

Indianapolis, IN · On-site +1

ML Engineering and MLOps practices. * LangChain, LlamaIndex, Haystack, or similar frameworks. * PostgreSQL database administration and optimization. * Vector databases such as pgvector, Chroma ...

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All JobsMlops Engineer JobsMlops Engineer Jobs in Indiana

Mlops Engineer information

See Indiana salary details

$94.2K

$147.9K

$171.6K

How much do mlops engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for mlops engineer in Indiana is $147,859.00, according to ZipRecruiter salary data. Most workers in this role earn between $142,021.00 and $159,363.00 per year, depending on experience, location, and employer.

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

What is an MLOps Engineer job?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in machine learning deployment, cloud platforms, and automation tools can earn $300,000 or more annually. High compensation is often associated with roles in large tech companies, specialized expertise, and leadership responsibilities.

What engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, and machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Roles often require expertise in cloud platforms, programming, and system architecture, along with strong project management abilities.

What are some common challenges Mlops Engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive in the Mlops Engineer position, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
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Mlops Engineer jobs near you

Data Systems/Solutions Engineer

RR

Indianapolis, IN • On-site

$109K - $131K/yr

Full-time

Life, Retirement, PTO

Posted 7 days ago

Job description

Position Summary
The Data Systems / Solutions Engineer serves as a key technical contributor within the Regenstrief Data Services team, functioning as a full-stack DataOps/MLOps engineer supporting research and analytics initiatives. This role is responsible for designing, building, and maintaining scalable, reliable data systems and pipelines that enable high-quality data ingestion, transformation, storage, and analysis.
The position emphasizes the development of robust, secure, and reproducible data infrastructure that supports data science, analytics, and AI-driven research. The Engineer applies modern software engineering and data engineering practices to ensure data assets are accessible, well-governed, and aligned with clinical and research requirements.
This position is a hybrid position with at least one (1) to two (2) days of onsite activity based on business needs. This position is located in downtown Indianapolis IN.
Essential Duties and Responsibilities
Data Systems Engineering and Operations:
  • Design, build, and maintain data platforms, pipelines, and services that support research, analytics, and AI/ML workloads.
  • Develop and maintain scalable data architectures using modern data warehouse/lakehouse patterns.
  • Ensure data systems are reliable, performant, and designed for long-term sustainability.
  • Implement and maintain ETL/ELT workflows, data validation, and quality monitoring processes.

DataOps / MLOps Enablement:
  • Implement CI/CD practices for data and ML workflows, including testing, version control, and environment promotion.
  • Support reproducible analytics and ML pipelines, including experiment tracking and model lifecycle considerations.
  • Apply best practices for monitoring, observability, and incident response across data systems.

Cloud, Security, and Governance
  • Design and maintain cloud-based data solutions using secure and scalable architectural patterns.
  • Apply data governance, access control, and auditing practices consistent with HIPAA-aligned research environments.
  • Ensure appropriate handling of sensitive data through de-identification, access management, and compliance controls.
  • Optimize performance and cost efficiency across compute and storage resources.

Clinical and Research Data Support
  • Work with clinical and research stakeholders to translate domain requirements into technical solutions.
  • Support integration and use of clinical and biomedical data standards (e.g., EHR data, HL7/FHIR, OMOP).
  • Produce well-documented data assets and technical specifications to support reuse and transparency.

Collaboration and Project Support
  • Collaborate with data engineers, researchers, analysts, and project managers to deliver high-quality solutions.
  • Contribute to project planning, estimation, and execution.
  • Serve as a technical resource to team members and stakeholders.
  • Document systems, workflows, and architectural decisions clearly and consistently.

Continuous Learning and Innovation
  • Maintain current knowledge of emerging tools, technologies, and best practices in data engineering and AI.
  • Leverage AI-assisted development tools responsibly to improve productivity and code quality.
  • Participate in continuous improvement efforts across systems, processes, and workflows.

Knowledge, Skills, and Abilities
Technical Knowledge:
  • Proficiency in modern data engineering concepts, including:
    • Data warehouse and lakehouse architectures
    • Dimensional modeling and data transformation patterns
    • SQL and at least one general-purpose programming language (e.g., Python)
  • Experience with CI/CD pipelines and automated testing for data and ML workflows
  • Familiarity with data quality frameworks, lineage tracking, and observability tools
  • Understanding of cloud platforms, identity and access management, and security best practices
  • Knowledge of clinical and biomedical data standards and research workflows preferred

Analytical and Problem-Solving Skills
  • Ability to analyze complex technical problems and implement effective solutions
  • Strong troubleshooting skills across data ingestion, transformation, and delivery layers
  • Ability to balance reliability, performance, and cost considerations

Communication and Collaboration
  • Strong written and verbal communication skills
  • Ability to document technical concepts clearly for both technical and non-technical audiences
  • Demonstrated ability to collaborate effectively in multidisciplinary teams

Education and Experience
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field required; Master's degree preferred.
  • Minimum of three (3) years of professional experience in data engineering, systems engineering, or a related technical role.
  • Demonstrated experience in:
    • Data platform or data pipeline development
    • Cloud-based data system
    • SQL and programmatic data processing
    • DataOps or MLOps practices

Performance Expectations
  • Works independently within established guidelines and best practices.
  • Produces high-quality work with minimal supervision.
  • Demonstrates sound judgment and attention to detail.
  • Contributes to continuous improvement of tools, processes, and team effectiveness.

Physical Demands
  • Ability to work standard business hours with flexibility as needed.
  • Ability to sit or stand for extended periods.
  • Ability to operate a computer and standard office equipment.
  • Ability to lift and move materials up to 20 pounds as needed.
  • Ability to travel occasionally for meetings or training.

Work Environment
  • Hybrid office and research environment.
  • Fast-paced, deadline-driven setting.
  • Requires collaboration with internal teams and external partners.
  • Regular use of computers, communication tools, and office equipment.

BENEFITS OF WORKING HERE
  • Work with a variety of diverse professionals in the healthcare industry
  • Free parking
  • Paid holidays, vacation, and sick time
  • Group Life and Voluntary Term Life insurance
  • Long-term and Short-term Disability plans
  • Employee Assistance Program (EAP)
  • Flexible Spending Account (FSA)
  • 403b Retirement Plan with gracious employer contributions
  • Fitness program
  • Pet insurance
  • Qualified employer for loan forgiveness

Please note sponsorship and/or relocation are not available for this position.
REGENSTRIEF INSTITUTE REQUIRES ALL EMPLOYEES TO RECEIVE THE INFLUENZA VACCINATION ANNUALLY UNLESS APPROVED FOR EXEMPTION.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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