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Ml Engineer Jobs in Florida (NOW HIRING)

Catalyst Labs

ML Engineer

Miami, FL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Tampa, FL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Catalyst Labs

ML Engineer

Jacksonville, FL · On-site

They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to ...

Rempli

AI / ML Engineer

Miami, FL · On-site

$95K - $150K/yr

AI / ML Engineer We partner withcompanies pushing the boundaries of technology - and we'relooking for AI / ML Engineers who are passionate about buildingintelligent systems that solve real-world ...

Accenture Federal Services

AI/ML Engineer

Tampa, FL · Hybrid

Apply core software engineering and ML fundamentals to ensure performance, reliability, and security (e.g., data structures, algorithms, model evaluation, MLOps, API development). * Implement and ...

Luma Financial Technologies, LLC

AI/ML Engineer

Miami, FL · On-site

$100 - $130/hr

About the role We are seeking a talented AI/ML Engineer with a minimum of 3 years of hands‑on experience in the AI/ML domain. This exciting opportunity, based in India and reporting to the Software ...

Accenture Federal Services

AI/ML Engineer

Tampa, FL · Hybrid

$108K - $185K/yr

Apply core software engineering and ML fundamentals to ensure performance, reliability, and security (e.g., data structures, algorithms, model evaluation, MLOps, API development). * Implement and ...

Accenture Federal Services

AI/ML Engineer

Tampa, FL · On-site

$108K - $185K/yr

Apply core software engineering and ML fundamentals to ensure performance, reliability, and security (e.g., data structures, algorithms, model evaluation, MLOps, API development). * Implement and ...

Career Launch

Founding AI/ML Engineer

Miami, FL · On-site

$120 - $190/hr

THE ROLE As a Founding AI/ML Engineer, you may work on projects that require strong execution, communication, analytical judgment, and the ability to move quickly in ambiguous environments. This ...

Tenex

AI/ML Engineer II

Sarasota, FL · On-site

$120 - $150/hr

As an AI/ML II Engineer at TENEX, you will be a key technical contributor responsible for designing, developing, and optimizing scalable, high-performance AI systems. You will play a crucial role in ...

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Ml Engineer information

See Florida salary details

$24.7K

$66.6K

$106.1K

How much do ml engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for ml engineer in Florida is $66,646.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,700.00 and $81,500.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.

What are the most commonly searched types of Ml Engineer jobs in Florida?

The most popular types of Ml Engineer jobs in Florida are:

What are popular job titles related to Ml Engineer jobs in Florida?

For Ml Engineer jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Ml Engineer jobs in Florida look for?

The top searched job categories for Ml Engineer jobs in Florida are:

What cities in Florida are hiring for Ml Engineer jobs?

Cities in Florida with the most Ml Engineer job openings:

Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Florida as of August 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $66,646 per year, or $32 per hour.

ML Engineer

Miami, FL • On-site

Catalyst Labs
See more jobs at Catalyst Labsexternal

Full-time

Re-posted 24 days ago

Job description

Job Summary:
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. They are seeking an ML Engineer to design, build, and deploy production-grade ML systems, focusing on audio data and real-time audio understanding, while collaborating with cross-functional teams to drive innovation in AI applications.
Responsibilities:
• Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle from conception to deployment and maintenance.
• Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
• Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
• Build agents capable of operating natively on real-world audio inputs.
• Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
• Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
• Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
• Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 1-6 years of professional experience in ML engineering.
• Strong programming skills in Python (TypeScript experience is a plus).
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Familiarity with cloud environments and infrastructure (preferably AWS).
• Strong understanding of data pipeline design, real-time inference, and model monitoring.
• Excellent communication skills with the ability to engage directly with customers and stakeholders.
• Proven experience building and deploying ML models into production environments.
• Demonstrated ability to own the full model lifecycle from data ingestion and model development to deployment and monitoring.
• Experience with audio-focused ML projects or similar domains involving unstructured data.
• Proficiency in building scalable data pipelines for model training and evaluation.
• Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
Preferred:
• Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
Company:
Welcome to Catalyst Labs – Powering Catalytic Growth At Catalyst Labs, catalytic growth isn't just a concept, it's our driving force. Founded in , the company is headquartered in London, GB, , with a team of 11-50 employees. The company is currently Early Stage.

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