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Machine Learning Manager Jobs in Orlando, FL (NOW HIRING)

Experiencedeploying production-ready machine learning models * Experience withModel explainability (SHAP, LIME)or similar * Experience with cloud cost management and practices (e.g., Azure Cost ...

Industry/Sector Not Applicable Specialism Data Science Management Level Manager & Summary At PwC ... Those in data science and machine learning engineering at PwC will focus on leveraging advanced ...

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ... Non-Management Exempt Workshift: 1st Shift (United States of America) Job Family: IFT > Artificial ...

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ... Excellent written & verbal communication and stakeholder management skills. * 4+ years project ...

Data Scientist

Orlando, FL · On-site

$107K/yr

Technical Leadership & Mentorship (10%) • Lead and manage a pipeline of talent, including interns ... Proficiency with data mining, statistical analysis, and machine learning platforms (e.g., AzureML ...

Data Science Tutor

Orlando, FL · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Developing machine learning models for liquid-solid, solid-solid, and gas-solid interfaces ... Managing collaborations with other research teams (internal and external) * Mentoring graduate and ...

... machine learning models • Experience with Model explainability (SHAP, LIME) or similar • Experience with cloud cost management and practices (e.g., Azure Cost Management, chargeback/show back ...

AI DevOps Engineer (AWS)

Orlando, FL

$49.25 - $67.50/hr

... Machine Learning, data platforms, or MLOps environments, with strong scripting skills in Python and/or Bash. * Experience implementing monitoring, observability, IAM, secrets management, cloud ...

AI DevOps Engineer (AWS)

Orlando, FL

$49.25 - $67.50/hr

... Machine Learning, data platforms, or MLOps environments, with strong scripting skills in Python and/or Bash. * Experience implementing monitoring, observability, IAM, secrets management, cloud ...

Lead ML Ops Engineer

Orlando, FL · 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 ...

Sales Manager

Orlando, FL · On-site

$80K - $225K/yr

If you have any prior experience in sales, recruitment, HR technology, or machine learning ... Current Sales Managers who plug into our system, engage in self-development, and focus on core ...

Showing results 21-40

Machine Learning Manager information

See Orlando, FL salary details

$47.6K

$76.3K

$110.2K

How much do machine learning manager jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning manager in Orlando, FL is $76,276.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,600.00 and $86,400.00 per year, depending on experience, location, and employer.

What are some of the main challenges a machine learning manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

Is machine learning a high paying job?

Machine Learning Managers typically earn high salaries due to their specialized skills in data analysis, programming, and model development. Compensation varies based on experience, location, and industry, but it is generally considered a well-paying role within the tech sector.

What are the key skills and qualifications needed to thrive as a machine learning manager?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What is a machine learning manager?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.

What are the most commonly searched types of Machine Learning jobs in Orlando, FL?

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

What are popular job titles related to Machine Learning Manager jobs in Orlando, FL?

For Machine Learning Manager jobs in Orlando, FL, the most frequently searched job titles are:

What cities near Orlando, FL are hiring for Machine Learning Manager jobs?

Cities near Orlando, FL with the most Machine Learning Manager job openings:

Director of Manufacturing Technology

CIG COMPANIES SERVICES

Orlando, FL

Full-time

Posted 24 days ago


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.