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

Seeking a Machine Learning Engineer for the following role - Generative AI & ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, Diffusers Training: DeepSpeed, Accelerate, Ray, distributed ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Senior ML Platform Engineer Job at a Glance * Title: Senior ML Platform Engineer * Location ... The ideal candidate is someone who builds and supports the platform that enables machine learning ...

New

AI Solutions Engineering Delivery Lead

Orlando, FL · On-site

$95K - $126K/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 information

See Kissimmee, FL salary details

$27.8K

$113.8K

$171K

How much do machine learning engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for machine learning engineer in Kissimmee, FL is $113,781.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,700.00 and $137,000.00 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 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 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 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.

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 are the most commonly searched types of Machine Learning Engineer jobs in Kissimmee, FL?

The most popular types of Machine Learning Engineer jobs in Kissimmee, FL are:

What are popular job titles related to Machine Learning Engineer jobs in Kissimmee, FL?

For Machine Learning Engineer jobs in Kissimmee, FL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Kissimmee, FL look for?

The top searched job categories for Machine Learning Engineer jobs in Kissimmee, FL are:

What cities near Kissimmee, FL are hiring for Machine Learning Engineer jobs?

Cities near Kissimmee, FL with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Kissimmee, FL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $113,781 per year, or $54.7 per hour.

Sr Machine Learning Engineer

Orlando, FL • On-site

$135K - $181K/yr

Other

Posted 15 days ago


Key responsibilities

  • Owns the design and development of machine learning models, pipelines, and production ML systems.

  • Drives development of ML components through own and other engineers' work.

  • Interacts and coordinates deliverables with data science, data engineering, and product teams across the organization.


Job description

Job Posting Title: Sr Machine Learning Engineer Req ID: 10154204 Job Description: The Senior Machine Learning Engineer applies practical knowledge of machine learning, data science, and software engineering to conceive, design, develop, train, and deploy ML models, pipelines, and systems of moderate to high complexity. The Senior Machine Learning Engineer owns the design and development of ML solutions and drives their delivery through their own and other engineers’ work. The Senior Engineer provides technical guidance and acts as a point of escalation and as a machine learning expert. The Senior Machine Learning Engineer designs and develops highly scalable ML systems and data pipelines.

Responsibilities
  • Owns the design and development of machine learning models, pipelines, and production ML systems.
  • Drives development of ML components through own and other engineers’ work.
  • Develops technical solutions that meet specifications and that inform future ML initiatives.
  • Executes assigned ML development projects and major model improvements using new or existing technologies.
  • Develops specifications for assigned ML components, projects, or model enhancements.
  • Reviews and writes code for model training, evaluation, and inference pipelines.
  • Participates in setting the architectural direction for ML platforms and data infrastructure.
  • Designs specific ML components for assigned projects, developing specifications for each.
  • Able to build and lead end-to-end ML workflows from data ingestion through model serving.
  • Interacts and coordinates deliverables with data science, data engineering, and product teams across the organization.
  • Designs and develops ML system specifications for assigned projects.
  • Designs component tasks for assigned projects, developing ML-specific specifications for each.
  • Serves as a high-level technical resource and “go-to” person for less experienced ML engineers and data scientists, providing technical guidance and oversight.
  • Leads team members in problem analysis, model debugging, and issue resolution.
Basic Qualifications
  • 5+ years of relevant experience designing, training, and deploying machine learning models in production environments at scale.
  • Experience with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Strong understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.
  • Strong expertise in MLOps practices including model versioning, experiment tracking, CI/CD for ML, and model monitoring.
  • Experience with cloud-based ML services and infrastructure (e.g., AWS SageMaker, EC2, S3).
  • Experience with data pipeline and orchestration tools (e.g., Airflow, Spark, Kafka).
  • Familiarity with database and data storage technologies (e.g., DynamoDB, Redshift, NoSQL), containerization (Docker, Kubernetes), and data manipulation tools.
  • Experience with Snowflake is required.
Preferred Qualifications
  • Experience with large-scale recommendation systems, personalization, NLP, or computer vision.
  • Experience with real-time ML inference and low-latency serving architectures.
  • Familiarity with LLMs and generative AI integration in production systems.
  • Experience with Java (e.g., Spring Boot) is a plus.
Required Education

Bachelor’s degree in Computer Science, Statistics, Mathematics, or similar field, or related work experience.

The hiring range for this position in Florida is $135,200.00-$181,200.00 per year.

The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors.

A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Job Posting Segment: DX Technology

Job Posting Primary Business: Commerce

Job Posting Primary Job Posting Category: Machine Learning

Employment Type: Full time

Primary City, State, Region, Postal Code: Orlando, FL, USA

Alternate City, State, Region, Postal Code:

Date Posted: 2026-06-29

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