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Mlops Data Engineer Jobs in Utah (NOW HIRING)

Pwc

ERP AI Engineer - Manager

Salt Lake City, UT

$99K - $232K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

In Oracle data and analytics at PwC, you will utilise Oracle's suite of tools and technologies to ... with MLOps tooling and CI/CD pipelines for ML - Experience with vector databases and semantic ...

Amh

Product Engineering Architect

Draper, UT · On-site

  • Dental

  • Vision

  • Retirement

  • PTO

Leverages deep expertise in Generative AI, Agentic AI systems, LLM orchestration, and MLOps ... Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or a related field or ...

Cisco

Applied AI Scientist

Lehi, UT

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Collaborate with engineering, product, and data science teams to understand requirements ... MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates ...

Cisco

Applied AI Scientist

Salt Lake City, UT

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Collaborate with engineering, product, and data science teams to understand requirements ... MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates ...

Deloitte

Google AI Lead Architect

Salt Lake City, UT · On-site

$53.50 - $73.25/hr

Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build. * Lead cloud-native ...

Zions Bank

AI Solutions Architect

Midvale, UT · On-site

$59.50 - $78.25/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with Enterprise Architects, Data Scientists, and Engineering teams to architect and launch ... MLOps/LLMOps strategy. * Enhance the Enterprise Architecture practice by designing forward-looking ...

Enterprise Technology Operations

AI Solutions Architect

Midvale, UT · Hybrid

$59.50 - $78.25/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with Enterprise Architects, Data Scientists, and Engineering teams to architect and launch ... MLOps/LLMOps strategy. * Enhance the Enterprise Architecture practice by designing forward-looking ...

Zions Bancorporation

AI Solutions Architect

Midvale, UT · On-site

$59.50 - $78.25/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with Enterprise Architects, Data Scientists, and Engineering teams to architect and launch ... MLOps/LLMOps strategy. * Enhance the Enterprise Architecture practice by designing forward-looking ...

Zions Bancorporation

AI Solutions Architect

Midvale, UT · On-site

$150 - $210/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with Enterprise Architects, Data Scientists, and Engineering teams to architect and launch ... MLOps/LLMOps strategy. * Enhance the Enterprise Architecture practice by designing forward-looking ...

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Showing results 41-57

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Utah

Mlops Data Engineer information

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Utah?

For Mlops Data Engineer jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Utah look for?

The top searched job categories for Mlops Data Engineer jobs in Utah are:

What cities in Utah are hiring for Mlops Data Engineer jobs?

Cities in Utah with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Logan, UT • On-site

Other

Re-posted 28 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

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

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply