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

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 ...

Raft

ML Ops Engineer

Tampa, FL · On-site

... operations. Qualifications : Required : • 3+ years of relevant hands-on experience • Experience building and maintaining machine learning pipelines • Strong Python skills for defining and ...

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 ...

Amgen

Principal Software Engineer

Tampa, FL

$127K - $171K/yr

Yourexpertisein 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 ...

Amgen, Inc.

Principal Software Engineer

Tampa, FL · On-site

$127K - $171K/yr

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 ...

Lincare Holdings, Inc.

Data Scientist

Clearwater, FL · On-site

Experience in developing Machine Learning Models/ LLMs, streamlining ETL operations, Database management and Predictive analytics Preferred Physical Demands: The employee may frequently lift and/or ...

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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 Aug 9, 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.

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

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.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks above average compared to other tech roles.
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Tampa, FL as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 4% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $78,411 per year, or $37.7 per hour.

Bigdata Engineer

Disys - Oak Brook

Tampa, FL • On-site

$52.75 - $69.75/hr

Contractor

Re-posted 23 days ago

Job description

Company Description
Job Description
Position Details:
Job Title: Bigdata Engineer
Location: Tampa, FL
Duration: 12+ Months Contract to hire
Job Responsibilities:
Principal Responsibilities
• Design interfaces to the data warehouses/data storages and machine learning/Big Data
• applications using open source tools such as Scala, Java, Python, Perl and shell scripting.
• 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 Scientist teams to ensure data
• pipelines and processes fit within the production framework.
• Ensure that tools and environments adhere to strict security protocols.
• Deploy the machine learning model and serve its outputs as RESTful API calls.
• Understand the business needs in close collaborations with subject matter experts (SMEs)
• and Data Scientists to do efficient feature engineering for machine learning models.
• Maintain the code and libraries in code repository.
• Work with system administration team to proactively resolve issues/install tools and libraries
• on the AWS platform.
• Research and come up with architecture and solutions most appropriate for problems at hand.
• Maintain and improve tools to assist Analytics in ETL, retrospective testing, efficiency,
• repeatability, and R&D.
• Lead by example regarding software best practices, including code style and architecture,
• documentation, source control, and testing.
• Support the Chief Data Scientist/Data Scientists/Big Data Engineers in creating new and novel
• approaches to solve challenging problems using Machine Learning, Big Data and Cloud
• technologies.
• Handle ADHOC requirements to create reports for the end users.
Required Skills
• Strong skills with Apache Spark (Spark SQL) and SCALA with at least 2+ years of experience.
• Understanding of AWS Big Data components and tools.
• Strong Java skills with experience in web services and web development is required.
• Hands on experience with model deployment.
• Hands on experience in application deployment on Docker and/or Kubernetes or other similar technology.
• Linux scripting is a plus.
• Fundamental understanding of AWS cloud components.
• 2+ years of experience in data ingesting, cleansing/processing, storing and querying large datasets
• 2+ years of experience in engineering large-scale data solutions with Java/Tomcat/ SQL/Linux
• Experience working in a data intensive role including the extraction of data (db/web/api/etc.), transformation and loading (ETL)
• Exposure with structured and/or unstructured data contents
• Experience with data cleansing/preparation on Hadoop/Apache Spark Ecosystem - MapReduce/Hive/HBase/Spark SQL
• Experience with distributed streaming tools like Apache KAFKA.
• Experience with multiple file formats (Parquet, Avro, OCR)
• Knowledge in AGILE development cycle.
• Efficient coding skills to enhance the performance/cost savings of the job running on AWS platform.
• Experience in building stable, scalable, and high-speed live streams of data and serving web platforms
• Enthusiastic self-starter with ability to work in a team environment.
• Graduate (MS) or Undergraduate degree in Computer Science/ Engineering/relevant field
Nice to have:
• Strong Software development experience
• Machine Learning model deployment experience
• Ability to write custom Map/Reduce programs to clean/prepare complex data
• Familiarity with Streaming data processing - Experience with distributed real time computation system like Apache STORM/Apache Spark Streaming.
Qualifications
Additional Information
All your information will be kept confidential according to EEO guidelines.

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