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Quantum Machine Learning Engineer Jobs in Port Charlotte, FL

Quantum Machine Learning Engineer information

See Port Charlotte, FL salary details

$26K

$106.3K

$159.7K

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

As of Sep 3, 2026, the average yearly pay for quantum machine learning engineer in Port Charlotte, FL is $106,264.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,800.00 and $127,900.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

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

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, focusing on developing algorithms that leverage quantum hardware. The field is emerging with high growth potential, requiring skills in quantum algorithms, programming languages like Python, and understanding of both quantum mechanics and machine learning principles. As quantum technology advances, demand for specialists in this area is expected to increase, making it a promising career path for those with relevant expertise.

What cities near Port Charlotte, FL are hiring for Quantum Machine Learning Engineer jobs?

Cities near Port Charlotte, FL with the most Quantum Machine Learning Engineer job openings:

Full-time

Re-posted 27 days ago


Roper Technologies rating

8.7

Company rating: 8.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

56th of 247 rated software companies


Job description

Roper Technologies is seeking a Machine Learning Engineer to help design, build, and deploy advanced AI systems across our portfolio of market-leading software businesses. 
This role will focus on developing scalable machine learning products and services, shared AI components, and intelligent agents that drive meaningful business impact. Depending on experience level, the role may involve leading architectural initiatives, mentoring engineers, and shaping technical strategy. 
 
We are looking for hands-on engineers who are excited about building production-grade AI systems—not just prototypes—and who thrive in a high-impact, applied environment. Candidates who have demonstrated ability to think through product as well as engineering are highly desired.
 
What You’ll Do 
 
AI & ML System Development 
  • Design, build, and deploy machine learning models and AI systems in production environments 
  • Develop components such as:
    • Model inference services 
    • Data and feature pipelines
    • Complex recommendation and matching services
    • Vision based analysis systems
    • Evaluation and monitoring pipelines 
  • Optimize models for performance, reliability, and cost efficiency      
Intelligent Agents & Applied AI 
  • Contribute to the development of AI agents and multi-step workflow automation systems 
  • Build systems that integrate with enterprise tools and APIs 
  • Implement tool-use frameworks, memory mechanisms, and evaluation loops 
  • Experiment with LLMs, foundation models, and fine-tuning approaches 
  • Help translate AI research advances into practical, scalable solutions 
Engineering Excellence 
  • Write high-quality, maintainable, and well-tested code 
  • Participate in architecture design and technical reviews 
  • Contribute to CI/CD pipelines and MLOps workflows 
  • Implement observability and monitoring for AI systems in production 
  • Follow security, compliance, and responsible AI best practices 
Cross-Functional Collaboration 
  • Partner with product, data engineering, and infrastructure teams 
  • Help identify high-impact AI use cases within portfolio companies 
  • Support integration of shared AI components into business applications 
  • Communicate technical tradeoffs clearly to both technical and non-technical stakeholders 
Qualifications 
 
We welcome candidates across a range of experience levels. The scope and seniority of responsibilities will scale accordingly.  
Required 
  • 3+ years of experience in software engineering, data science, or machine learning (more for senior roles) 
  • Experience building and deploying production software systems 
  • Strong programming skills in Python (experience in additional languages is a plus) 
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) 
  • Understanding of modern AI architectures, including LLM-based systems 
  • Experience working with cloud environments (AWS, Azure, or GCP) 
  • Strong problem-solving skills and attention to detail 
 
Preferred  
  • Experience with:
    • Fine tuning, experimentation, etc.
    • Rapid development using AI tools 
    • Agent frameworks and orchestration tools 
    • Distributed systems or microservices architecture 
    • Model monitoring and evaluation frameworks 
  • Experience building reusable libraries or shared infrastructure 
  • Exposure to SaaS products or enterprise software environments 
  • Background in optimizing models for performance and cost
Leveling & Growth 
 
We are hiring across multiple experience levels: 
  • Intermediate ML Engineer – Contributes independently to projects, builds production features, collaborates cross-functionally. 
  • Senior ML Engineer – Owns complex systems end-to-end, drives architectural decisions, mentors others. 
  • Principal / Staff ML Engineer – Defines technical direction, leads cross-portfolio initiatives, designs shared frameworks and scalable AI infrastructure. 
Level and compensation will be determined based on experience and demonstrated expertise. 
 
What We Value 
  • Strong engineering fundamentals 
  • Practical, impact-driven AI development 
  • Curiosity and willingness to experiment responsibly 
  • Ownership mindset and bias toward execution 
  • Ability to balance innovation with reliability 
Why Join Roper 
  • Work on high-impact AI systems across a diverse portfolio of leading software businesses 
  • Build reusable infrastructure that scales across industries 
  • Collaborate with experienced engineering and executive leadership 
  • Shape the next generation of intelligent enterprise software 

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