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Machine Learning Engineer Opt Jobs in Tampa, FL (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Tampa, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Tampa, FL

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

OneBlood

AI & Machine Learning Engineer

Saint Petersburg, FL · On-site

$105K - $127K/yr

Five (5) or more years of experience in data engineering, data science, or a related role, with hands-on experience in building and deploying machine learning models. CERTIFICATES, LICENSES ...

OneBlood

AI & Machine Learning Engineer

Saint Petersburg, FL · On-site

$105K - $127K/yr

Five (5) or more years of experience in data engineering, data science, or a related role, with hands-on experience in building and deploying machine learning models. CERTIFICATES, LICENSES ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Tampa, FL

Machine Learning Engineer Opt information

See Tampa, FL salary details

$29.8K

$121.7K

$182.9K

How much do machine learning engineer opt jobs pay per year?

As of Aug 9, 2026, the average yearly pay for machine learning engineer opt in Tampa, FL is $121,689.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,900.00 and $146,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Tampa, FL? For Machine Learning Engineer Opt jobs in Tampa, FL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Tampa, FL look for? The top searched job categories for Machine Learning Engineer Opt jobs in Tampa, FL are:
What cities near Tampa, FL are hiring for Machine Learning Engineer Opt jobs? Cities near Tampa, FL with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

Machine Learning Engineer

Revenue Management Solutions

Tampa, FL • Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New

Job description

THE OPPORTUNITY

As a machine learning engineer, you will have the opportunity to learn and apply RMS’ methodologies to solve analytical problems critical to driving high-end business value to our clients. This position requires basic knowledge of Data Science methods and a strong, applied knowledge of Python and SQL. Experience deploying models in cloud-based environments is desired.

RIGHT TO WORK

Candidates must have the legal right to work in the country the position is based. The employer does not provide sponsorship for work authorization for this role.


WHO YOU’LL WORK WITH

You’ll work with as part of our Research & Development team, reporting to the Senior Director of AI and Machine Learning. We take pride in encouraging each other’s career ambitions and you’ll find opportunities for personal development throughout our company. This is a hybrid position, working in the office 3 days a week.

WHAT YOU’LL DO

  • Monitor model performance both pre- and post-deployment
  • Develop pipelines to collect, transform, and aggregate data
  • Work with CI/CD pipelines to create and deploy artifacts
  • Refactor code to perform efficiently in scaled environments
  • Creatively design solutions to analytical problems using quantitative and qualitative approaches to drive high-end business value
  • Develop and maintain documentation articulating methodology and architecture, as well as data dictionaries
  • Effectively and concisely articulate processes to internal parties


SKILLS AND QUALIFICATIONS

  • Strong knowledge with Python, including experience building custom packages
  • Experience with Scala or Spark will be considered an asset
  • Some cloud-based experience; Azure preferred
  • Ability to manage multiple projects independently
  • Working knowledge of statistics, machine learning and deep-learning algorithms
  • 2+ Years Experience
  • Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a field with a quantitative and technical emphasis required


PREFERRED

  • Graduate degree, or supplementary courses in Data Science, Data Engineering or Machine Learning

BENEFITS

as a full-time RMS Employee, you will be eligible for:

  • 100% employer paid HSA medical insurance, or 80% employer paid medical insurance for HMO and PPO plans for employees and qualifying dependents
  • Dental and vision insurance (80% employer paid)
  • Basic Life and AD&D insurance (100% employer paid)
  • Telemedicine (100% employer paid)
  • 401k plan with company matching contribution of 4% of annual gross salary with immediate vesting
  •  Tuition assistance is available to support continuous education efforts
  • 15 business days paid vacation for the first year based on your hire date (pro rata), 15 days thereafter; 20 days after two years, and 25 days after ten years
  • Eight paid holidays + 1 personal floating holiday
  • Paid parking and health club membership
  • Paid parental leave

WHO WE ARE

Now more than ever, Revenue Management Solutions (RMS) is committed to supporting restaurants through these ever-changing times. Today, more than 50 major brands in over 40 countries trust RMS for data-driven analytics and tech-enabled solutions to optimize sales, menus and a brand’s financial health. Six of the top 10 US fast food brands and 16 of the top 30 global restaurant brands (equaling more than 100,000 restaurants) rely on RMS’ software solutions and actionable insights to make informed business decisions that drive profitability and combat inflation and increasing wages. The company holds five US patents on menu pricing and customer segmentation and supports ongoing academic research efforts. For more information on how RMS helps its clients, visit revenuemanage.com.

WHAT WE BELIEVE

Our goal at RMS is to create a positive change in the communities we inhabit. With over 20 countries represented throughout our offices, we respect and embrace different cultures, interests, and actions. The acknowledgment of our unique identities is something that connects us across continents to uphold our values of diversity, respect, and responsibility.

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