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Mlops Junior Jobs in Boca Raton, FL (NOW HIRING)

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$7

$25

$44

How much do mlops junior jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for mlops junior in Boca Raton, FL is $25.58, according to ZipRecruiter salary data. Most workers in this role earn between $15.53 and $31.49 per hour, depending on experience, location, and employer.

What is an MLOps junior?

MLOps Junior roles focus on supporting the deployment, maintenance, and monitoring of machine learning models in production environments. As a junior professional, you typically assist in automating workflows, managing data pipelines, and collaborating with data scientists and engineers. Responsibilities often include configuring cloud resources, setting up CI/CD pipelines, and ensuring models run smoothly after deployment. It's an entry-level position that helps bridge the gap between data science and operations, providing hands-on experience with machine learning infrastructure.

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

To thrive as an MLOps Junior, you need a solid understanding of machine learning principles, programming in Python, and knowledge of software development practices, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), containerization tools (like Docker), CI/CD pipelines, and version control systems (like Git) is typically required. Strong problem-solving, collaboration, and a willingness to learn stand out as soft skills in this role. These skills and qualities are crucial for efficiently deploying, maintaining, and scaling machine learning models in real-world production environments.

What are some common challenges faced by a junior MLOps professional in their first year, and how can they overcome them?

As a Junior MLOps professional, one of the main challenges is bridging the gap between data science and engineering practices, particularly when deploying machine learning models to production. You may encounter issues like automating model pipelines, managing dependencies, and ensuring reproducibility. Collaborating closely with data scientists, software engineers, and DevOps teams is essential for learning best practices and troubleshooting problems efficiently. Proactively seeking mentorship, participating in code reviews, and familiarizing yourself with popular MLOps tools (such as Docker, Kubernetes, and CI/CD platforms) can greatly accelerate your growth and confidence in the role.

What is the difference between Mlops Junior vs Data Engineer?

AspectMlops JuniorData Engineer
Required CredentialsBasic understanding of ML workflows, some certifications preferredDegree in Computer Science or related field, certifications in data management
Work EnvironmentCollaborates with data scientists and ML engineers in tech companiesWorks on data pipelines, storage, and processing systems in various industries
Industry UsageEmerging role in AI/ML teams, startups, and tech firmsEstablished role across finance, healthcare, tech, and more

The comparison shows that Mlops Junior and Data Engineer roles share some technical foundations but differ mainly in focus. Mlops Junior emphasizes deploying and maintaining ML models, while Data Engineers focus on building data infrastructure. Both roles are vital in data-driven organizations, with Mlops Junior often working closely with Data Engineers to ensure smooth ML operations.

Is MLOps a good career choice in 2026?

MLOps Junior roles are expected to remain in demand in 2026 due to the growing adoption of machine learning and AI across industries. These roles typically require skills in cloud platforms, automation, and tools like Docker and Kubernetes, making them a promising career path for those interested in AI deployment and infrastructure. Continuous learning and certification in relevant technologies can enhance job prospects in this field.

Is MLOps in high demand?

MLOps junior roles are in high demand as organizations increasingly adopt machine learning and AI solutions. These positions require skills in cloud platforms, automation, and tools like Docker and Kubernetes, reflecting the growing need for efficient deployment and management of ML models across industries.

What are the most commonly searched types of Mlops jobs in Boca Raton, FL?

The most popular types of Mlops jobs in Boca Raton, FL are:

What job categories do people searching Mlops Junior jobs in Boca Raton, FL look for?

The top searched job categories for Mlops Junior jobs in Boca Raton, FL are:

What cities near Boca Raton, FL are hiring for Mlops Junior jobs?

Cities near Boca Raton, FL with the most Mlops Junior job openings:

Mlops Junior jobs near you
Infographic showing various Mlops Junior job openings in Boca Raton, FL as of June 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Temporary. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $53,207 per year, or $25.6 per hour.

Junior/Middle Computer Vision Engineer ID72410

AgileEngine, LLC.

Boca Raton, FL • On-site

$70 - $100/hr

Other

Posted 11 days ago

Job description

Full time | AgileEngine | United States

Posted On 08/20/2026

Job Information

City Boca Raton

State/Province Florida

33427

IT Services

Job Description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands‑on AI experience.

WHAT YOU WILL DO
  • Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality;
  • Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently;
  • Document training results, maintain ongoing evaluation benchmarks, and track model performance over time;
  • Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement;
  • Take ownership of foundational tasks that support the broader team’s AI/ML lifecycle, directly contributing to the speed and success of production deployments.
MUST HAVES
  • You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
  • 1 to 3 years of experience in software engineering, data science, machine learning, or a related field;
  • Degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience);
  • Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
  • Foundational coding skills in Python;
  • Foundational understanding of machine learning concepts and workflows;
  • Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
  • Basic familiarity with cloud environments and compute resources;
  • A strong, demonstrable willingness to learn and adapt in a fast‑paced, mentorship‑driven environment;
  • Excellent attention to detail, specifically regarding data quality and documentation;
PERKS AND BENEFITS
  • Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
  • Exciting projects: Modern solutions with Fortune 500 and top product companies.
  • Flextime: Flexible schedule with remote and office options.
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