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Machine Learning Engineer Python Jobs in Apopka, FL

Deloitte

GenAI Data Scientist

Lake Mary, FL

Build and prioritize backlog for future machine-learning enabled features to support client ... Bachelor's degree or equivalent experience * 6+ years of experience programming in in Python or R ...

Deloitte

GenAI Data Scientist

Lake Mary, FL · On-site

Build and prioritize backlog for future machine-learning enabled features to support client ... Bachelor's degree or equivalent experience * 6+ years of experience programming in in Python or R ...

Kavaliro

Full Stack Engineer

Orlando, FL · On-site

Design, develop, and maintain end-to-end software solutions using Java, C, and Python . * Develop ... Experience with data pipelines , machine learning integration , or IoT platforms is a plus.

Guru Schools

Senior/Lead AI Engineer

Orlando, FL · On-site

Python (preferred), TypeScript/Node.js for integrations. * Cloud Platforms: Azure AI/ML services ... MLOps: MLflow, Azure Machine Learning, or equivalent model lifecycle tools. * Observability:

DPR Construction

MLOps Engineer

Orlando, FL

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Siemens Energy, Inc.

AI Engineer

Orlando, FL · On-site

Large language models (LLM), generative AI, NLP, and machine learning * Frameworks and patterns ... Proficiency in Python, API development, and application design * AWS and/or Azure deployment and ...

Leidos

AI Data Science Intern

Orlando, FL · On-site

$48.10K - $86.95K/yr

... programming languages (e.g., Python , Java , C++ , JavaScript ) Preferred Qualifications * Coursework, projects, or hands-on experience in areas such as: * Artificial Intelligence or Machine Learning

Ucf

Post Doctoral Scholar

Orlando, FL · On-site

$57K/yr

Conduct cutting-edge research in AI, machine learning, and multimodal learning, with a focus on ... Programming Proficiency: Strong programming skills in Python, with experience in deep learning ...

Leidos

AI Data Science Intern

Orlando, FL · On-site

$48.10K - $86.95K/yr

... programming languages (e.g., Python , Java , C++ , JavaScript ) Preferred Qualifications * Coursework, projects, or hands-on experience in areas such as: * Artificial Intelligence or Machine Learning

Pwc

Google Cloud Architect - Senior Manager

Orlando, FL · On-site

$124K - $280K/yr

... Machine Learning Engineer Professional, Cloud DevOps Engineer Professional - Proficiency in Java 8 or Python design and development - Skilled in Microservices REST API and Event Driven Design ...

INSPYR Solutions

Data Scientist

Orlando, FL · On-site

$45 - $51/hr

Must have experience and proficiency using machine learning platforms (e.g., AzureML), process ... programming tools (e.g., SQL, Python, etc.), business intelligence/data visualization software ...

Pwc

CTIO-AI Engineer-Sr Associate

Orlando, FL · On-site

$55K - $187K/yr

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 ...

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Machine Learning Engineer Python information

See Apopka, FL salary details

$20.2K

$122.7K

$177.5K

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

As of May 30, 2026, the average yearly pay for machine learning engineer python in Apopka, FL is $122,686.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $144,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What cities near Apopka, FL are hiring for Machine Learning Engineer Python jobs? Cities near Apopka, FL with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
GenAI Data Scientist

GenAI Data Scientist

Deloitte

Lake Mary, FL

Other

Posted 25 days ago

Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services

Job description

Our Deloitte AI & Engineering team to transform technology platforms, drive innovation, and help make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

Work You'll Do

As a US Delivery Center Senior Solution Specialist on the team, you will:

  • Work across client teams to develop and architect Generative AI solutions using ML and GenAI
  • Develop and promote standards across the community
  • Evaluate and select appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies
  • Work with leadership and stakeholders to identify AI opportunities and promote strategy.
  • Develop and conduct trainings for users across the Government & Public Services landscape on principles used to develop models and how to interact with models to facilitate their business processes.
  • Build and prioritize backlog for future machine-learning enabled features to support client business processes.
  • Design and build generative models, selecting the most suitable architecture (e.g., GANs, VAEs) based on the desired output (text, images, code). This involves writing code using Python libraries like TensorFlow or PyTorch.

The Team

Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

Qualifications

Required: 

  • Bachelor's degree or equivalent experience
  • 6+ years of experience programming in in Python or R with libraries like TensorFlow, PyTorch, or Keras
  • 5+ years of experience with Natural Language Processing (NLP) and Large Language Models (LLM) 
  • 5+ years of experience building and maintaining scalable API solutions
  • 5+ years of experience in data wrangling/cleansing, statistical modeling, and programming
  • 5+ years of extensive experience working in an Agile development environment
  • 3+ years of solid understanding of machine learning algorithms, including supervised and unsupervised learning
  • 3+ years of deep learning architectures like convolutional neural networks (CNNs) for image generation and recurrent neural networks (RNNs) for text generation are key areas of focus.
  • 3+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches likePrompt Engineering, fine-tuning, etc.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future 
  • Must be able to obtain and maintain the required clearance for this role 
  • Delivery Center Location & Travel Requirements:
    • Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, or Mechanicsburg) 
    • Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
    • Travel Requirement: Maximum of 10% overnight travel for client or project purposes
    • Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred: 

  • Understanding how to apply these models for tasks like text generation, image creation, or data augmentation is essential.
  • Understanding language modeling concepts like n-grams and how they relate to LLM training is important.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure can be helpful for deploying and scaling LLM models, especially for large datasets.
  • Knowledge of NLP techniques like text pre-processing, tokenization, and sentiment analysis can be valuable for crafting effective prompts.
  • In depth understanding of AI protocols and standards
Qualifications:

Our Deloitte AI & Engineering team to transform technology platforms, drive innovation, and help make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

Work You'll Do

As a US Delivery Center Senior Solution Specialist on the team, you will:

  • Work across client teams to develop and architect Generative AI solutions using ML and GenAI
  • Develop and promote standards across the community
  • Evaluate and select appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies
  • Work with leadership and stakeholders to identify AI opportunities and promote strategy.
  • Develop and conduct trainings for users across the Government & Public Services landscape on principles used to develop models and how to interact with models to facilitate their business processes.
  • Build and prioritize backlog for future machine-learning enabled features to support client business processes.
  • Design and build generative models, selecting the most suitable architecture (e.g., GANs, VAEs) based on the desired output (text, images, code). This involves writing code using Python libraries like TensorFlow or PyTorch.

The Team

Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

Qualifications

Required: 

  • Bachelor's degree or equivalent experience
  • 6+ years of experience programming in in Python or R with libraries like TensorFlow, PyTorch, or Keras
  • 5+ years of experience with Natural Language Processing (NLP) and Large Language Models (LLM) 
  • 5+ years of experience building and maintaining scalable API solutions
  • 5+ years of experience in data wrangling/cleansing, statistical modeling, and programming
  • 5+ years of extensive experience working in an Agile development environment
  • 3+ years of solid understanding of machine learning algorithms, including supervised and unsupervised learning
  • 3+ years of deep learning architectures like convolutional neural networks (CNNs) for image generation and recurrent neural networks (RNNs) for text generation are key areas of focus.
  • 3+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches likePrompt Engineering, fine-tuning, etc.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future 
  • Must be able to obtain and maintain the required clearance for this role 
  • Delivery Center Location & Travel Requirements:
    • Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, or Mechanicsburg) 
    • Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
    • Travel Requirement: Maximum of 10% overnight travel for client or project purposes
    • Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred: 

  • Understanding how to apply these models for tasks like text generation, image creation, or data augmentation is essential.
  • Understanding language modeling concepts like n-grams and how they relate to LLM training is important.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure can be helpful for deploying and scaling LLM models, especially for large datasets.
  • Knowledge of NLP techniques like text pre-processing, tokenization, and sentiment analysis can be valuable for crafting effective prompts.
  • In depth understanding of AI protocols and standards
Education:OtherEmployment Type:

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