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Assistant Mlops Jobs in Indiana (NOW HIRING)

3B Staffing LLC

MLOps Engineer

Indianapolis, IN · On-site

The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of ... Data Management and Collaboration: • Assist as needed with data labeling and management, ensuring ...

3B Staffing LLC

MLOps Engineer

Indianapolis, IN · On-site

The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of ... Data Management and Collaboration: • Assist as needed with data labeling and management, ensuring ...

Munich Re

Technical Architect - Data, Analytics & AI

Fishers, IN · Hybrid

$57.50 - $73.75/hr

  • Medical

  • Life

  • Retirement

  • PTO

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap ... Exposure to AI/ML concepts , including model development, deployment, monitoring, and MLOps ...

Munich Re

Technical Architect - Data, Analytics & AI

Fort Wayne, IN · Hybrid

$58.75 - $75.50/hr

  • Medical

  • Life

  • Retirement

  • PTO

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap ... Exposure to AI/ML concepts , including model development, deployment, monitoring, and MLOps ...

Munich Re

Technical Architect - Data, Analytics & AI

Carmel, IN · Hybrid

$63.75 - $81.75/hr

  • Medical

  • Life

  • Retirement

  • PTO

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap ... Exposure to AI/ML concepts , including model development, deployment, monitoring, and MLOps ...

Munich Re

Technical Architect - Data, Analytics & AI

Evansville, IN · Hybrid

$60.75 - $78.25/hr

  • Medical

  • Life

  • Retirement

  • PTO

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap ... Exposure to AI/ML concepts , including model development, deployment, monitoring, and MLOps ...

Deloitte

AI Engineer Consultant

Indianapolis, IN · Hybrid

Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants ... LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version ...

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Assistant Mlops information

What is an Assistant MLOps?

Assistant MLOps are professionals who support the deployment, monitoring, and management of machine learning models in production environments. They assist senior MLOps engineers with tasks like automating workflows, managing data pipelines, maintaining infrastructure, and ensuring model performance. Their role bridges the gap between data science and IT operations, helping organizations scale and maintain their AI solutions efficiently. Assistant MLOps often have knowledge of cloud services, CI/CD tools, and basic programming, and they work closely with data scientists and engineers.

What is the difference between Assistant Mlops vs Data Engineer?

AspectAssistant MlopsData Engineer
Required CredentialsCertifications in cloud platforms, basic scripting, ML toolsComputer science degree, SQL, Python, data architecture
Work EnvironmentCollaborates with ML teams, supports deployment pipelinesBuilds data pipelines, manages databases, processes large datasets
Industry UsageAI/ML projects, cloud-based environmentsData infrastructure, analytics, big data solutions

Assistant Mlops and Data Engineer roles share overlapping skills in cloud platforms and scripting. However, Assistant Mlops focuses on supporting ML deployment and operations, while Data Engineers primarily build and maintain data infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are the typical daily responsibilities of an Assistant MLOps?

As an Assistant MLOps professional, you can expect your daily tasks to involve supporting the deployment, monitoring, and maintenance of machine learning models in production environments. This often includes collaborating with data scientists to automate model training and testing workflows, managing cloud-based resources, and ensuring that data pipelines are running smoothly. You'll also help troubleshoot issues related to model performance or infrastructure and assist in implementing best practices for version control and continuous integration. Working closely with both engineering and data teams, you'll play a key role in ensuring that ML models remain reliable and scalable in real-world applications.

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

To thrive as an Assistant MLOps, you need a solid understanding of machine learning fundamentals, programming (especially Python), and experience with cloud platforms; a degree in computer science or a related field is typically preferred. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git) is important, and certifications in cloud services (AWS, Azure, GCP) can be advantageous. Strong problem-solving, communication, and collaboration skills help you bridge the gap between data science and operations teams. These combined skills ensure efficient deployment, monitoring, and maintenance of machine learning models in production environments.

Is assistant MLOps in high demand?

Assistant MLOps roles are increasingly in demand as organizations expand their machine learning and AI initiatives. These positions often require knowledge of cloud platforms, automation tools, and deployment pipelines, reflecting the growing need for scalable and reliable ML systems across industries.

What are the most commonly searched types of Mlops jobs in Indiana?

The most popular types of Mlops jobs in Indiana are:

What are popular job titles related to Assistant Mlops jobs in Indiana?

For Assistant Mlops jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Assistant Mlops jobs in Indiana look for?

The top searched job categories for Assistant Mlops jobs in Indiana are:

What cities in Indiana are hiring for Assistant Mlops jobs?

Cities in Indiana with the most Assistant Mlops job openings:

Assistant Mlops jobs near you

MLOps Engineer

3B Staffing LLC

Indianapolis, IN • On-site

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

We are seeking a dynamic Software Engineer with an ML focus to lead the integration and operationalization of machine learning models in our Search area. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse ML platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of our ML infrastructure.
Hands-on experience working on recommender systems, drawing from ML techniques such as embedding based retrieval, reinforcement learning, and transformers.
• Software engineering skills to work with teams integrating the recommender systems into customer facing products.
• Experience in AB testing and iterative optimization using data driven approaches.
• Understanding of infrastructure needs required to deploy ML systems (CPU/GPU, networking infrastructure).
Feature Store Management:
• Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
• Implement feature stores as a central repository for maintaining transparency in ML operations across the organization.
• Enable feature delivery with endpoint exposure while maintaining authority and security features.
Data Management and Collaboration:
• Assist as needed with data labeling and management, ensuring high-quality data for ML models.
• Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in ML models.
• Ensure end-to-end integration for data to AI, including the use of BigTable / BigQuery for executing machine learning models on business intelligence tools.
Continuous Monitoring and Optimization:
• Monitor ML systems in production, identify improvement opportunities, and implement optimizations.
• Participate in support rotations and participate in support calls, as necessary.

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