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Computer Vision Object Detection Jobs (NOW HIRING)

eStaffLLC

Senior Software Developer Specialist

Austin, TX · On-site

$54 - $71.25/hr

Computer Vision Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference. MLOPS & INFRASTRUCTURE MLOps Tools: Production experience with ...

eStaffLLC

Senior Software Developer Specialist

Austin, TX · On-site

$54 - $71.25/hr

Computer Vision Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference. MLOPS & INFRASTRUCTURE MLOps Tools: Production experience with ...

eStaffLLC

Senior Software Developer Specialist

Austin, TX · On-site

$54 - $71.25/hr

Computer Vision Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference. MLOPS & INFRASTRUCTURE MLOps Tools: Production experience with ...

InnovationTeam

Junior AI Engineer - Computer Vision

Requirements • Develop and train Computer Vision models for image and video analysis. • Implement solutions for object detection, image classification, segmentation, and tracking. • Prepare and ...

Cesna Group

Computer Vision R&D Engineer

San Diego, CA · On-site

$100K - $200K/yr

... object detection, image processing, denoising, segmentation and metrology. * - Research, develop and employ machine learning algorithms for solving difficult and exciting challenges. * - Engineer ...

Clarium

Senior Software Engineer, Computer Vision

$170K - $210K/yr

This role owns the end-to-end pipeline: object detection, identification, reconciliation, and data ... computer vision and object detection * Hands-on experience training and fine-tuning detection ...

Vizor

AI Automation & Engineering Intern

New York, NY · On-site

$20/hr

Work on robotic picking, lightweight computer vision, automated packaging, and labeling systems * Train, refine, and deploy object detection models for product identification, robotic picking ...

Merlin Labs

Computer Vision Engineer

Boston, MA · On-site

$121K - $142K/yr

Develop and implement object detection and identification algorithms for real-time applications ... Proficiency with computer vision libraries and frameworks (OpenCV, PyTorch/TensorFlow, CUDA)

TEEMA

Computer Vision Engineer

San Diego, CA · On-site

$125K - $130K/yr

Develop real-time algorithms for object detection, tracking, pose estimation, and motion analysis ... or related field * 3+ years of computer vision experience in real-time, product-focused ...

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All JobsComputer Vision Object Detection Jobs

Computer Vision Object Detection information

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$18

$53

$76

How much do computer vision object detection jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for computer vision object detection in the United States is $53.11, according to ZipRecruiter salary data. Most workers in this role earn between $41.11 and $68.51 per hour, depending on experience, location, and employer.

What is Computer Vision Object Detection?

Computer Vision Object Detection is a field within artificial intelligence and computer science that focuses on enabling computers to identify and locate objects within digital images or videos. Using advanced algorithms and deep learning models, object detection systems can recognize multiple objects, determine their positions, and classify them into predefined categories. Applications of object detection include autonomous vehicles, surveillance systems, medical imaging, and retail analytics. Its effectiveness depends on the quality and diversity of the training data, as well as the complexity of the algorithms used.

Is CV a part of ML?

Computer Vision (CV) is a field within artificial intelligence that often overlaps with machine learning (ML). Many CV applications, such as object detection, rely on ML algorithms like deep learning to analyze and interpret visual data. Professionals in computer vision frequently use ML frameworks like TensorFlow or PyTorch to develop models.

Is computer vision a dead field?

Computer vision object detection remains a highly active area within AI, with ongoing research and industry applications such as autonomous vehicles, security, and healthcare. Professionals in this field use skills in deep learning, neural networks, and tools like OpenCV and TensorFlow, and demand continues to grow as technology advances.

Is Yolo considered AI?

YOLO (You Only Look Once) is a real-time object detection algorithm used in computer vision, which is a subset of artificial intelligence. As part of computer vision tasks, it employs machine learning techniques to identify and classify objects in images or videos, making it a form of AI technology relevant to roles like computer vision object detection.

What are the key skills and qualifications needed to thrive as a Computer Vision Object Detection specialist, and why are they important?

To thrive in Computer Vision Object Detection, you need strong programming skills (especially in Python), a solid background in machine learning and deep learning, and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience using annotation tools and cloud platforms, is crucial. Strong problem-solving ability, attention to detail, and effective communication skills help you design robust models and collaborate with multidisciplinary teams. These skills are essential for developing accurate and efficient object detection systems that address real-world challenges in industries like automotive, healthcare, and security.

Is ML a high paying job?

Machine learning (ML) roles, including those in computer vision object detection, are generally well-paid due to high demand for specialized skills such as programming, data analysis, and experience with frameworks like TensorFlow or PyTorch. Salaries vary based on experience, location, and industry, but professionals with advanced skills in ML can earn competitive compensation packages. Certifications and a strong portfolio can also enhance earning potential in this field.

How does a Computer Vision Object Detection specialist typically collaborate with software engineers and data scientists on projects?

In most organizations, Computer Vision Object Detection specialists work closely with software engineers and data scientists to integrate detection models into larger applications. They often collaborate on data collection and annotation, model training and tuning, and deploying solutions at scale. Regular cross-functional meetings and code reviews are common, ensuring that models meet performance requirements and align with broader product goals. Effective communication and teamwork are essential, as the role often involves translating technical model outputs into actionable insights for various stakeholders.
Infographic showing various Computer Vision Object Detection job openings in the United States as of June 2026, with employment types broken down into 82% Full Time, 14% Part Time, 2% Contract, and 2% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $110,464 per year, or $53.1 per hour.

Senior Software Developer Specialist

eStaffLLC

Austin, TX • On-site

$54 - $71.25/hr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

We are seeking a Senior Software Developer for a hybrid position (2 days/wk in South Austin office) with deep expertise in AI/ML development to join our Austin client's team. In this role, you will design, build, and deploy production-grade machine learning systems that serve real users on a scale. You will work across cloud platforms, contribute to MLOps infrastructure, and collaborate with cross-functional teams to deliver impactful AI-driven solutions.

CORE REQUIREMENTS AI/ML SPECIALIZATIONS Natural Language Processing & LLMs Experience with transformer architectures (BERT, GPT, T5), RAG systems, fine-tuning, prompt engineering, or building LLM applications. Time Series & Anomaly Detection Forecasting models, anomaly detection, sequential data modeling, or real-time monitoring systems. Recommender Systems * Collaborative filtering, ranking models, personalization engines, or content recommendation pipelines.

Computer Vision Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference. MLOPS & INFRASTRUCTURE MLOps Tools: Production experience with MLflow, Weights & Biases, Kubeflow, Airflow, or equivalent platforms. * Distributed Training: Large-scale model training, multi-GPU/multi-node setups, and efficient data parallelism.

CI/CD: Azure DevOps, GitHub Actions, Jenkins, or comparable automation pipeline experience. Feature Stores: Familiarity with Feast, Tecton, or advanced feature engineering practices. * Model Optimization: Quantization, pruning, and knowledge distillation for production efficiency.

LLM Models: Experience with Ollama, Hugging Face, or other open/non-frontier model frameworks. Required Technical Skills Python: 3-5+ years of production experience; Python is your primary language. * AI/ML Production: Built and deployed 2-3+ ML models serving real users - not just experiments.

Cloud Platforms: Experience with AWS, Azure, GCP, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major providers (Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, OCI AI Services). DevOps: Hands-on experience with Ansible, CI/CD pipelines, Docker, and Kubernetes.

Databases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL/vector databases. Scripting: Proficient in both Bash and PowerShell for automation workflows. Preferred Qualifications * Experience with Geospatial Information Systems (GIS) and analyzing spatial data.

Prior experience in transportation, logistics, or smart city sectors. Background in Computer Vision (object detection, image segmentation) applied to infrastructure or vehicular data. * Familiarity with public sector data compliance, security, and governance standards.

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