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Machine Learning Engineer Jobs in Winter Springs, FL

Data Scientist

Orlando, FL ยท On-site +1

Looking for candidate making a career in Data Science with experience applying advanced statistics, data mining and machine learning algorithms to make data-driven predictions using programming ...

Lead ML Ops Engineer

Orlando, FL ยท On-site

$95K - $126K/yr

This role manages a team of Machine Learning Operations Engineers, oversees the endtoend machinelearning strategy and execution, sets vision for MLOps, and ensures alignment with business goals. How ...

US Tech - AI Engineering Manager

Orlando, FL ยท On-site

$73K - $244K/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 ...

Be Seen First

Strong Python programming skills with hands-on experience building, training, deploying, and monitoring machine learning models. * Solid experience with SQL (2+ years) for database querying, data ...

Be Seen First

Strong Python programming skills with hands-on experience building, training, deploying, and monitoring machine learning models. * Solid experience with SQL (2+ years) for database querying, data ...

Showing results 21-40

Machine Learning Engineer information

See Winter Springs, FL salary details

$26.9K

$110.2K

$165.5K

How much do machine learning engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for machine learning engineer in Winter Springs, FL is $110,154.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,800.00 and $132,600.00 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 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 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.

What are popular job titles related to Machine Learning Engineer jobs in Winter Springs, FL? For Machine Learning Engineer jobs in Winter Springs, FL, the most frequently searched job titles are:
What cities near Winter Springs, FL are hiring for Machine Learning Engineer jobs? Cities near Winter Springs, FL with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Winter Springs, FL as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 100% In-person job distribution, with an average salary of $110,154 per year, or $53 per hour.

Data Scientist

(unknown company)

Orlando, FL โ€ข On-site, Remote

Full-time

Re-posted 10 days ago


Job description

Company Description
We are passionate people with an expert understanding of the digital consumer, data sciences, global telecom business, and emerging financial services. And we believe that we can make the world a better place.
Job Description
Looking for candidate making a career in Data Science with experience applying advanced statistics, data mining and machine learning algorithms to make data-driven predictions using programming languages like Python (including: Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn), SQL (Postgresql). Experience with ElasticSearch, information/document retrieval, natural language processing is a plus. Experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods, outlier analysis) and parameters that affect their performance also helps. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
Qualifications
Qualifications
โ€ข Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
โ€ข At least 2 years' of experience in quantitative analytics or data modeling
โ€ข Some understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
โ€ข Fluency in these programming languages (Python, SQL), Javascript/HTML/CSS/Web Development nice to have.
โ€ข Familiarity with data science frameworks and visualization tools (Pandas, Visualizations (matplotlib, altair, etc), Jupyter Notebooks)
Additional Information
Responsibilities
โ€ข Analyze raw data: assessing quality, cleansing, structuring for downstream processing
โ€ข Design accurate and scalable prediction algorithms
โ€ข Collaborate with engineering team to bring analytical prototypes to production
โ€ข Generate actionable insights for business improvements
tion will be kept confidential according to EEO guidelines.