ZipRecruiter

Log In

1

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

Software Technology Inc

ML Engineer

Pensacola, FL · On-site

ML Engineer Location: CA, WA, FL, NY (Disney Hubs) - Onsite Orlando, Florida San Francisco ... Machine learning, and deep learning techniques, exploratory data analysis (EDA), data science Key ...

Persona AI

Software Engineering Intern

Pensacola, FL · On-site

We're seeking a Software Engineering Intern to join our team in Houston, TX or Pensacola, FL and ... Machine Learning : Implement learning algorithms, training pipelines, and model optimization for ...

Persona AI

Robotics Simulation Engineer

Pensacola, FL · On-site

You will report to the Behavior Coordination Lead and work closely with machine learning, locomotion, manipulation, perception, and devops teams. Your Role: * Build, maintain, and extend simulation ...

Dtcc

Lead Platform Engineer*

Pensacola, FL · Hybrid

$96K - $127K/yr

You will benefit from our structured training programs, peer mentorship, and access to internal learning community as you continue to build on your foundational software engineering skills. DTCC is ...

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Milton, FL

Machine Learning Engineer information

See Milton, FL salary details

$28.2K

$115.4K

$173.4K

How much do machine learning engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for machine learning engineer in Milton, FL is $115,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,900.00 and $138,900.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies 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 they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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.

More about Machine Learning Engineer jobs
What are popular job titles related to Machine Learning Engineer jobs in Milton, FL? For Machine Learning Engineer jobs in Milton, FL, the most frequently searched job titles are:
What cities near Milton, FL are hiring for Machine Learning Engineer jobs? Cities near Milton, FL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Milton, FL as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $115,362 per year, or $55.5 per hour.

Robotics Machine Learning Engineer

Persona AI

Pensacola, FL • On-site

Other

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

Job description

We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are primarily interested in candidates who have developed and released products to market, but can be flexible depending on aptitude and energy.
As one of the inaugural Machine Learning Engineers at Persona, you will have an incredible opportunity to get in at the beginning to shape the design and development of Persona's humanoid robot.
Your Role:

  • Collaborate on the design and development of the Persona ML software stack and support its application in manipulation, navigation, locomotion, and perception.
  • Work with the ML team to craft and execute on a comprehensive plan for the development of machine learning models, keeping up to date with the state of the art in research and development.
  • Work with the team to develop, test, and deploy software, machine learning pipelines, and data collection pipelines.
  • Monitor and evaluate the performance of models in the real world.
  • Collaborate with Universities and other companies.
  • Collaborate in attracting, nurturing and growing the machine learning and autonomy teams.
We're Looking For:
  • Courage and grit to tackle some of the hardest problems in embodied AI.
  • Enthusiasm for working collaboratively in a high paced team environment.
  • 3+ years of experience in machine learning applied to robotics.
  • Experience with deep learning frameworks (Pytorch, JAX, TensorFlow, etc.)
  • Experience with cloud computing to develop models, store data, etc. (AWS, Azure, GCP)
  • Strong understanding of the state of the art research in robot learning (behavior cloning for manipulation, reinforcement learning for locomotion, world models, etc.).
  • Understanding of the challenges of deploying neural network models in the real world.
  • Experienced in deploying both traditional and learning based approaches for robotics.
  • Capable of writing high quality software.
  • Thrive in fast paced and ambiguous environments.
  • Strong first principles thinker.
Preferred or Bonus Qualifications:
  • An advanced degree (Masters or PhD) in computer science, robotics, machine learning, or another related field.
  • Published papers at top ML/Robotics conferences (ICML, ICRA, CoRL, RSS, NeurIPS).
  • Have deployed robots, collected large amounts of data, and trained large neural networks that work in production environments.

Apply