ZipRecruiter

Log In

1

Machine Learning Operations Jobs in Tampa, FL (NOW HIRING)

Disys

Bigdata Engineer

Tampa, FL · On-site

$52.75 - $69.75/hr

Design and create data pipelines to maintain stable dataflow to the machine learning models - both in batch mode and near real-time mode. Interface with Engineering/Operations/System Admin/Data ...

Disys - Oak Brook

Bigdata Engineer

Tampa, FL · On-site

$52.75 - $69.75/hr

... machine learning models - • both in batch mode and near real-time mode. • Interface with Engineering/Operations/System Admin/Data Scientist teams to ensure data • pipelines and processes fit ...

MUFG

Senior Security Engineer - AI, Vice President

Tampa, FL · Hybrid

$108K - $148K/yr

... and tuning Machine Learning models for wide range of cyber security use cases. * Hands-on experience with atleast on the cloud AI solution (AWS Bedrock/SageMaker, Azure AI) * DevOps: Docker ...

next page

Showing results 1-20

All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in Tampa, FL

Machine Learning Operations information

See Tampa, FL salary details

$20

$37

$57

How much do machine learning operations jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for machine learning operations in Tampa, FL is $37.70, according to ZipRecruiter salary data. Most workers in this role earn between $31.59 and $40.00 per hour, depending on experience, location, and employer.

Is ML a high paying job?

Machine Learning Operations (MLOps) roles are generally well-paid due to the specialized skills required, such as expertise in cloud platforms, programming, and data management. Salaries tend to be higher than average tech roles and can increase with experience, certifications, and knowledge of tools like TensorFlow or Kubernetes.

What is the difference between Machine Learning Operations vs Data Scientist?

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

What engineer makes $500,000 a year?

Senior machine learning operations engineers with extensive experience, advanced skills in automation, cloud platforms, and deployment pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such roles often require expertise in tools like Kubernetes, Docker, and cloud services, along with strong problem-solving and leadership abilities.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, often found in large tech companies or innovative startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and overseeing complex models. AI may automate some routine aspects, but MLEs' expertise in data engineering, model optimization, and deployment remains critical for effective AI solutions.
Machine Learning Operations jobs near you
Principal Software Engineer - Tampa FL

Principal Software Engineer - Tampa FL

Veteran Jobs - 2023 Mar 01 - Veterans Resources

Tampa, FL • On-site

$127K - $171K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

 
ATTENTION MILITARY AFFILIATED JOB SEEKERS - Our organization works with partner companies to source qualified talent for their open roles. The following position is available to Veterans, Transitioning Military, National Guard and Reserve Members, Military Spouses, Wounded Warriors, and their Caregivers. If you have the required skill set, education requirements, and experience, please click the submit button and follow the next steps. Unless specifically stated otherwise, this role is On-Site at the location detailed in the job post.
 
 
What you will do
Let's do this. Let's change the world. In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. A background in data engineering, including experience with data pipelines and distributed data processing, is a strong plus. 
Roles & Responsibilities:  
Lead the end-to-end design, development, and delivery of machine learning and Generative AI (GenAI) solutions, from problem framing to production deployment and business impact realization.  
Act as the technical owner for large-scale ML/GenAI initiatives, driving architecture decisions, scalability, reliability, and long-term maintainability.  
Design and implement advanced agentic AI systems, including multi-agent architectures, reasoning workflows, tool integration, and autonomous decision-making systems.  
Define and institutionalize evaluation, validation, and governance frameworks for ML/GenAI systems, including model performance, prompt evaluation, safety guardrails, hallucination mitigation, and compliance.  
Partner directly with business stakeholders and product leaders to understand objectives, translate them into AI/ML solutions, and ensure measurable value delivery.  
Establish and enforce best practices in MLOps, LLMOps, and DevOps, including CI/CD, monitoring, observability, reproducibility, and cost optimization.  
Architect and oversee scalable cloud-based ML/GenAI platforms leveraging AWS, GCP, or Azure.  
Drive experimentation strategy, including A/B testing, prompt optimization, and iterative improvement of models and agent workflows.  
Provide technical leadership and mentorship to L4 and L5 engineers, including design reviews, code reviews, and career guidance.  
Lead cross-functional collaboration across data science, engineering, product, and business teams to deliver integrated AI solutions.  
Stay at the forefront of advancements in machine learning, Generative AI, and agentic systems, and drive adoption of new technologies and approaches.  
Design, develop, and implement robust data architectures and platforms to support ML Operation. 
Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring. 

Apply