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Machine Learning Engineer Opt Jobs in Edgewater, FL

Cloud think technologies LLC

AI Engineer

Lake Mary, FL · On-site

$60K - $135K/yr

Develop and implement AI solutions using advanced machine learning techniques and algorithms. Work with Large Language Models (LLM) to enhance natural language processing capabilities. Write ...

Deloitte

Data Scientist

Lake Mary, FL

... or Machine Learning role. * 5+ Years of Experience Proficiency in programming languages such as Python or R. * 5+ Years of Experience with Strong knowledge of machine learning techniques and ...

DataAnnotation

DevOps Engineer

Deltona, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

DataAnnotation

Software Engineer

Deltona, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

DataAnnotation

Frontend Engineer

Deltona, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

DataAnnotation

Mobile Software Engineer

Deltona, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Edgewater, FL

Machine Learning Engineer Opt information

See Edgewater, FL salary details

$28.5K

$116.4K

$174.9K

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

As of Jun 10, 2026, the average yearly pay for machine learning engineer opt in Edgewater, FL is $116,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,700.00 and $140,100.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What cities near Edgewater, FL are hiring for Machine Learning Engineer Opt jobs? Cities near Edgewater, FL with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

Senior Specialist, AI / Machine Learning Data Engineer

BNY

Lake Mary, FL

$107K - $141K/yr

Other

Posted 19 days ago

Job description

Senior Specialist, AI / Machine Learning Engineer

We're seeking a future team member for the role of Senior Specialist, AI / Machine Learning Engineer to join our AI Hub team. This role is located in Lake Mary, FL.

This role is located in our AI Hub and is focused on building AI-powered tools and platforms that improve the way engineers design, build, test, and operate software. This is an exciting opportunity for a strong individual contributor who can apply AI and software engineering skills to develop practical solutions, contribute to technical innovation, and help deliver scalable capabilities in support of engineering teams.

In this role, you'll make an impact in the following ways:

  • Design, develop, and support applied AI solutions, contributing hands-on to machine learning and artificial intelligence products and features.
  • Bring solid knowledge of Applied AI, LLMs, prompt engineering, fine tuning, model evaluation, and approaches to building fit-for-purpose models and copilots for engineering use cases.
  • Perform technical research, experimentation, and prototyping to evaluate tools, frameworks, and model approaches, and help translate results into implementation recommendations.
  • Partner with engineers and stakeholders to understand requirements, workflows, and user needs, and contribute to success measures that demonstrate solution value and adoption.
  • Apply AI to improve the software development lifecycle and support builders, designers, and developers through reliable, secure, and effective tools and capabilities.
  • Contribute to the achievement of Application Development objectives by delivering high-quality engineering work, supporting team standards, and continuously building technical depth across AI and software engineering practices.

To be successful in this role, we're seeking the following:

  • Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required.
  • 2-6 years of experience in software development required; experience in the securities or financial services industry is a plus.
  • Advanced experience, preferably 5+ years, in applied AI/ML, software engineering, or model development, including experience building and testing production-oriented solutions.
  • Ability to work independently as a strong technical contributor while collaborating closely with peers and senior engineers on solution design and delivery.
  • Strong understanding of software engineering fundamentals, enterprise development practices, and modern AI/ML tooling, with an interest in scalable and sustainable architectures.
  • Ability to communicate technical concepts clearly, learn quickly, and work effectively with both technical and non-technical stakeholders.

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