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Machine Learning Object Detection Jobs in Texas (NOW HIRING)

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Fine-tune and deploy computer vision and deep learning models for object detection, object tracking ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

New

Apple

Machine Learning Engineer

Austin, TX · On-site

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

PayPal

Machine Learning Engineer

Austin, TX

This job will validate and develop machine learning models and algorithms to solve complex problems ... Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or ...

WTS Paradigm LLC

Senior Applied ML Engineer

Irving, TX · On-site

$123K - $170K/yr

... Machine Learning, or related field. • 5+ years of experience designing and deploying applied ML systems at scale. • Experience with computer vision (CNNs, object detection, segmentation) and ...

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Machine Learning Object Detection information

What are the key skills and qualifications needed to thrive as a Machine Learning Object Detection Engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.
What are popular job titles related to Machine Learning Object Detection jobs in Texas? For Machine Learning Object Detection jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Object Detection jobs in Texas look for? The top searched job categories for Machine Learning Object Detection jobs in Texas are:
What cities in Texas are hiring for Machine Learning Object Detection jobs? Cities in Texas with the most Machine Learning Object Detection job openings:
Machine Learning Object Detection jobs near you

Machine Learning Engineer

Quarterhill

Frisco, TX • On-site

Full-time

Medical, Dental, Retirement, PTO

Posted 2 days ago

New

Job description

Overview
Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-artcomputer vision and language models that power scalable, real-world solutions. You'll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.
As part of our AI team, you'll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands-on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.
Responsibilities
  • Fine-tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop vision-language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrieval-Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and real-time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with cross-functional teams to integrate computer vision solutions into end-to-end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.
Qualifications
  • 5+ years of hands-on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrieval-Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.

Benefits
We offer a Total Rewards plan designed with you and your family's health and wellness in mind that includes:
  • Paid days off (i.e. vacation, sick days, bereavement leave)
  • Health and Dental plans
  • Retirement plans
  • Employee and Family Assistance Program (EFAP)
  • Employee referral program

We welcome applicants from all backgrounds, regardless of race, color, religion, sex, veteran status, sexual orientation, gender identity, national origin, age, or disability or any other protected characteristics in accordance with applicable federal, state/provincial, and local laws. We're committed to creating a workplace where everyone feels valued and respected.
We appreciate all responses and will acknowledge only those being considered for an interview.
We respectfully request no calls or unsolicited resumes from Agencies.

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