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Machine Learning Engineer Jobs in Lutz, FL (NOW HIRING)

Senior Cybersecurity Engineer - Tampa

Tampa, FL · Hybrid

$108K - $148K/yr

Senior Cybersecurity Engineer - Tampa Tampa, FL 33603 or Dallas, TX 75203 - Hybrid They offers a ... machine learning. RESPONSIBILITIES: * Responsible for providing 4th and 5th level support for ...

Design, develop, and deploy enterprise AI solutions spanning traditional machine learning ... Mentor junior AI engineers and elevate the broader organization's AI engineering capabilities

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Jr. Python Developer

Tampa, FL · On-site

$45.75 - $63/hr

Develop end-to-end Machine Learning prototypes and scale them to run in production environments ... Support projects and provide project status updates to project manager or Sr. Engineer * Partner ...

Agentic AI developer

Tampa, FL

$114K - $154K/yr

Experience designing and deploying machine learning systems across training, inference, and monitoring * Strong understanding of system architecture, distributed systems, and data engineering ...

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands. You will help shape ...

Data Engineer - Databricks

Tampa, FL · On-site

$108K - $129K/yr

We are seeking a Data Engineer with strong Databricks expertise to modernize and scale our Business ... This role will design and build data pipelines, deploy machine learning solutions, and ...

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Machine Learning Engineer information

See Lutz, FL salary details

$28.6K

$117.1K

$176K

How much do machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer in Lutz, FL is $117,093.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,300.00 and $140,900.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Machine Learning Engineer jobs in Lutz, FL look for? The top searched job categories for Machine Learning Engineer jobs in Lutz, FL are:
What cities near Lutz, FL are hiring for Machine Learning Engineer jobs? Cities near Lutz, FL with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Lutz, FL as of July 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $117,093 per year, or $56.3 per hour.
AIA COMMS ML Engineer

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Job description

Minimum of 4 years - Professional Experience in Coding Designing Developing and Analyzing Data in DS setting Create end to end ML workflow training pipelines engineer new features monitor training process unit testing Coding and architecting of end-to-end applications on modern data processing technology stack: Hadoop Hive AWS Cloud Spark ecosystem technologies Work on analytics application infrastructure analysis & requirements (e.g. configuration access tools
Hours : 8:00am to 5:00pm
Education :
Additional Job Details : Must Have Skills Google Cloud-Machine Learning