Search for Computer Vision Engineer roles in Orlando, Florida, focusing on deep learning and model deployment, with experience in YOLO and Kubernetes, and a preference for contract positions.

Okay, I've searched for Computer Vision Engineer roles in Orlando, Florida, emphasizing deep learning and model deployment, requiring experience with YOLO and Kubernetes, and available contract positions. I found 42 suitable openings for you.

Computer Vision Engineer

Orlando, FL

YOLO

Kubernetes

Contract

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The role of Computer Vision Pipeline Engineer at OP is fundamentally about merging advanced technical skills in deep learning with infrastructure engineering to develop robust, scalable, and efficient computer vision models. The focus is on deploying large-scale models like YOLO and OWL, which require not only proficiency in programming (particularly in Python and PyTorch) but also an adept understanding of MLOps and cloud environments. The primary responsibilities suggest a need for cross-functional collaboration, indicating that the individual must effectively communicate technical concepts to non-technical stakeholders while working closely with engineering, data science, and product teams. Success in this position is characterized by the ability to deploy models that perform well under real-world conditions, continually adapt to the latest research advancements, and contribute to the broader objectives of the organization by ensuring that these models enhance client offerings and operational efficiency. A strong background in hyperparameter tuning and experience with deployment tools will be crucial to overcoming technical challenges while driving innovation.

Company Analysis:

OP operates at the forefront of technology consulting, particularly in AI and cybersecurity, positioning itself as a disruptive force in a competitive marketplace. Its emphasis on out-of-the-box thinking and a lean model suggests a culture that thrives on rapid innovation and adaptability. This fast-paced and agile environment emphasizes the importance of creativity and collaboration, which impacts the role of a Computer Vision Pipeline Engineer significantly. The company values high performance and technical excellence, hinting at the expectation for employees to not only execute tasks efficiently but also contribute to knowledge-sharing and team cohesion. This role appears to have substantial visibility, collaborating with various teams and playing an essential part in strategic projects. The strategic alignment for this hire suggests that OP is looking to bolster its capabilities in delivering cutting-edge technology solutions that meet the increasing demands of its clientele, making it imperative for the new hire to be proactive and innovative in their approach.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Behavioral Questions:
1. Tell me about a time when you successfully deployed a complex machine learning model. What challenges did you face, and how did you overcome them?
1. Describe an instance when you had to work closely with a cross-functional team. How did you ensure that your technical contributions aligned with the broader project goals?
1. Can you provide an example of a project where you had to adapt quickly to a significant change in requirements or technology?
1. Discuss a situation where your innovative approach made a positive impact on a project outcome. What was your thought process?
Technical/Role-Specific Questions:
1. How would you approach optimizing a computer vision model for latency while maintaining accuracy?
1. What strategies would you use to manage and monitor model performance in a production environment?
1. Explain your experience with hyperparameter tuning. Can you walk us through a specific instance where you achieved significant improvements?
1. Describe how you would implement a deployment pipeline using Kubernetes for a computer vision application.
Situational Questions:
1. Imagine you are faced with conflicting feedback from different stakeholders about a deployed model’s performance. How would you handle this situation?
1. If you discovered a new research paper on a computer vision technique that could enhance your current project, how would you go about implementing it?
Company Fit/Motivation Questions:
1. What attracted you to OP, and how do you see yourself contributing to our fast-paced, innovative culture?
1. How do your professional values align with OP's mission to challenge the norms of consulting?
Questions for the Candidate to Ask the Interviewer:
1. Can you tell me about the types of projects the team is currently working on in relation to computer vision?
1. How does OP support the professional development of its engineers in keeping up with the latest technologies?
1. What does success look like for the Computer Vision Pipeline Engineer in their first 6-12 months?

Job Details

Overview Company

Computer Vision Pipeline Engineer

a day ago

Highlight

OnsiteContractorMid

Summary

OP is seeking a Computer Vision Pipeline Engineer to join their team in Orlando, FL. The role involves developing, experimenting with, and deploying state-of-the-art computer vision models.

About the Role

As a Computer Vision Pipeline Engineer, you will deploy large-scale computer vision models, design and implement training pipelines, perform hyperparameter tuning, and build tools for model evaluation. You will collaborate with cross-functional teams to integrate models into production systems and stay current with the latest CV research.

About You

Required:

Proficiency in Python and deep learning frameworks, especially PyTorch.
Strong hands-on experience with YOLO and OWL object detection models.
Solid understanding of computer vision tasks: object detection, segmentation, classification.
Experience deploying models using Kubernetes, Docker, and AWS SageMaker.
Familiarity with MLOps tools such as MLflow or Weights & Biases.
Expertise in Ubuntu/Linux environments for ML/AI experimentation and deployment.
Demonstrated success in hyperparameter tuning for large models.
Bachelor’s or Master’s in Computer Science, Machine Learning, or a related field.

Preferred:

Experience with real-time inference and edge deployment (e.g., TensorRT, ONNX Runtime, Jetson).
Familiarity with distributed training frameworks.

Benefits

401(k)
Dental insurance
Health insurance
Vision insurance

OP is one of the fastest-growing technology consulting and solutions companies in the U.S. We offer advisory and managed services, innovative platforms, and staffing solutions to help clients harness the power of technology for maximum impact. With broad and deep industry expertise, we deliver solutions across AI, cybersecurity, enterprise architecture, and beyond.

We don’t just consult—we challenge the norms of consulting. Our approach pairs out-of-the-box thinking with a radically lean model for faster, smarter, and more effective results.

At OP, our greatest strength is our people—bold thinkers, creative problem-solvers, and high performers who thrive in an agile, high-growth environment. Here, you won’t just access industry-leading strategies and technologies, you’ll help build them. You’ll learn, innovate, and push boundaries alongside an exceptionally talented team, shaping the future of our valued clients with every project.

Orlando, FL