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Machine Learning Robotics Jobs in Florida (NOW HIRING)

Serve Robotics

Partnership Manager

Miami, FL · On-site

$100K - $115K/yr

We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile ...

Serve Robotics

Operations Coordinator

Miami, FL · On-site

We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile ...

Serve Robotics

Operations Coordinator

Miami, FL · On-site

$23 - $25/hr

We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile ...

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Showing results 21-40

All JobsMachine Learning Robotics JobsMachine Learning Robotics Jobs in Florida

Machine Learning Robotics information

See Florida salary details

$19.1K

$31.8K

$65.8K

How much do machine learning robotics jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning robotics in Florida is $31,822.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,300.00 and $34,400.00 per year, depending on experience, location, and employer.

What is a machine learning robotics?

A Machine Learning Robotics job involves developing algorithms that enable robots to learn from data and improve their performance over time. Professionals in this field work on applications such as autonomous navigation, robotic perception, and human-robot interaction. They use techniques like deep learning, reinforcement learning, and computer vision to enhance a robot's ability to understand and interact with its environment. This role typically requires expertise in machine learning, robotics, and software development, along with strong problem-solving skills.

What are the key skills and qualifications needed to thrive in machine learning robotics?

To excel in Machine Learning Robotics, a strong background in computer science, robotics, and machine learning algorithms, often supported by a relevant degree (such as in engineering or computer science), is essential. Familiarity with programming languages like Python or C++, frameworks such as TensorFlow or ROS (Robot Operating System), and experience with simulation tools are highly valuable, and certifications in AI or robotics can further enhance employability. Strong problem-solving skills, effective communication, and the ability to work collaboratively in cross-disciplinary teams help professionals stand out. These capabilities are crucial for designing, developing, and refining intelligent robotic systems that perform reliably in real-world environments.

What are some common challenges faced by professionals working in machine learning robotics?

Professionals in Machine Learning Robotics often encounter challenges like integrating machine learning models with robotic hardware, ensuring reliable performance in unpredictable real-world settings, and managing computational limitations on embedded systems. Addressing these challenges usually requires creative problem-solving and close collaboration with hardware engineers, software developers, and data scientists. You may also need to continuously refine models and testing processes based on real-time feedback and evolving project goals. This dynamic environment makes the work both demanding and highly rewarding for those eager to push the boundaries of automation and intelligent systems.

What are the most commonly searched types of Machine Learning Robotics jobs in Florida?

The most popular types of Machine Learning Robotics jobs in Florida are:

What are popular job titles related to Machine Learning Robotics jobs in Florida?

For Machine Learning Robotics jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Machine Learning Robotics jobs in Florida look for?

The top searched job categories for Machine Learning Robotics jobs in Florida are:

Machine Learning Robotics jobs near you
Infographic showing various Machine Learning Robotics job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $31,822 per year, or $15.3 per hour.

Director of Manufacturing Technology

Orlando, FL • On-site

CIG COMPANIES SERVICES
See more jobs at CIG COMPANIES SERVICESexternal

Full-time

Re-posted 19 days ago

Key responsibilities

  • Define, deliver, and operate the manufacturing technology strategy to support manufacturing operations.

  • Own and provide strategic leadership for enterprise manufacturing application systems including ERP, MES, Supply Chain, and QMS.

  • Lead the adoption of advanced manufacturing technologies such as Industry 4.0, IoT, AI, and robotics to improve productivity and operational efficiency.

Job description

The Director of Manufacturing Technology is responsible for defining, delivering, and operating the technology strategy that enables world-class manufacturing operations across the organization's industrial businesses. This leader role serves as the strategic technology partner to Manufacturing and Operations leadership to ensure technology capabilities drive operational excellence, product quality, workforce productivity, and business growth.

The role owns the enterprise manufacturing application portfolio, including ERP manufacturing capabilities, Manufacturing Execution Systems (MES), Supply Chain systems, Warehouse Management, Quality Management Systems (QMS), Manufacturing Intelligence, Environmental Health & Safety systems, Learning & Training platforms, Product Lifecycle Management (PLM) integrations, and emerging Industry 4.0 technologies.

Working across multiple business units, the Director establishes common enterprise capabilities while enabling the unique operational requirements of each manufacturing business. The successful candidate combines deep manufacturing technology expertise with strong business acumen, enterprise architecture experience, and transformational leadership.

Key Responsibilities

Strategic Leadership

• Develop and execute the enterprise manufacturing technology strategy aligned with business objectives and digital initiatives.

• Serve as the trusted technology advisor to executive manufacturing and systems leadership.

• Build multi-year technology roadmaps supporting capacity expansion, operational excellence, automation, and digital manufacturing.

• Establish enterprise standards, governance, and best practices for manufacturing systems.

• Drive technology innovation while balancing operational stability, cybersecurity, cost, and business value.

Manufacturing Systems Leadership

Provide strategic ownership for enterprise manufacturing technology including:

Enterprise Resource Planning (ERP)

• Manufacturing

• Production Planning

• Material Requirements Planning (MRP)

• Shop Floor Integration

• Inventory Management

• Cost Accounting

• Procurement

• Supplier Collaboration

Manufacturing Execution Systems (MES)

• Production execution

• Work order management

• Electronic work instructions

• Genealogy and traceability

• Labor tracking

• Production line equipment integration

• Manufacturing data collection

• Performance analytics

Supply Chain Technology

• Supply Chain Planning

• Demand Planning

• Supplier Management

• Transportation Management

• Warehouse Management

• Inventory Optimization

• Procurement platforms

• Logistics visibility

Quality Management Systems (QMS)

• Incoming inspection

• Statistical Process Control (SPC)

• Nonconformance Management

• CAPA

• Audits

• Document Control

• Calibration

• Supplier Quality

• Regulatory Compliance

Environmental Health & Safety (EHS)

• Safety incident management

• Compliance reporting

• Hazard management

• Environmental compliance

• Risk assessments

• Safety observations

• Occupational health systems

Learning & Workforce Enablement

• Manufacturing training

• Learning Management Systems

• Skills certification

• Operator qualification

• Digital work instructions

• Knowledge management

Digital Manufacturing & Industry 4.0

Lead the adoption of advanced manufacturing technologies including:

• Industrial IoT

• Connected factory initiatives

• Machine connectivity

• Predictive maintenance

• Artificial Intelligence

• Machine Learning

• Robotics integration

• Digital twins

• Advanced analytics

• Computer vision

• Edge computing

• Manufacturing data platforms

Identify opportunities to improve productivity, quality, throughput, and operational efficiency through technology innovation.

Cybersecurity & Operational Technology

Partner closely with the parent company’s Cloud, Infrastructure, and Cybersecurity teams to:

• Protect manufacturing operations from cyber threats.

• Ensure compliance with industrial cybersecurity standards.

• Strengthen plant resiliency and disaster recovery.

• Manage risks associated with connected manufacturing equipment.

• Support regulatory and customer security requirements.

Qualifications

Education

• Bachelor's degree in Information Technology, Engineering, Computer Science, Manufacturing Engineering, Industrial Engineering, or related field.

• MBA or Master's degree preferred.

Experience

• 12+ years of progressive IT leadership experience supporting manufacturing organizations.

• 7+ years leading enterprise manufacturing technology teams.

• Experience supporting complex, multi-site manufacturing environments.

• Demonstrated success delivering enterprise ERP and MES implementations.

• Experience with supply chain and manufacturing transformation initiatives.

• Experience managing multimillion-dollar technology portfolios and budgets.

Preferred experience includes one or more of:

• Solar manufacturing

• Electronics manufacturing

• High-tech manufacturing

• Industrial manufacturing

• Automotive

• Aerospace

• Semiconductor

• Battery manufacturing

Technical Expertise

Strong knowledge of:

• Microsoft Dynamics 365 Business Central and F&O

• MES platforms 

• Supply Chain Planning solutions

• Warehouse Management Systems

• Product Lifecycle Management (PLM)

• Manufacturing Data Historians

• Quality Management Systems

• EHS platforms

• Learning Management Systems

• Industrial IoT platforms

• Cloud technologies 

• Integration platforms and APIs

• Manufacturing analytics and reporting

• Operational Technology (OT) environments

• Industrial networking and automation concepts

________________________________________

Success Measures

During the first 24 months, the Director will be expected to:

• Modernize the manufacturing technology roadmap across all production facilities.

• Improve manufacturing system reliability and availability to enterprise service-level targets.

• Increase plant productivity through digital manufacturing initiatives.

• Enhance manufacturing data quality and real-time operational visibility.

• Improve supply chain planning and inventory accuracy through integrated technology.

• Strengthen product traceability and quality compliance.

• Expand digital work instructions and workforce enablement capabilities.

• Improve cybersecurity posture across manufacturing environments.

• Standardize manufacturing technology governance across business units.

• Build a scalable technology organization capable of supporting future manufacturing growth.