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Machine Learning Object Detection Jobs in Northlake, TX

Photon

AI/ML Data Scientist | Onsite

Dallas, TX

Key Responsibilities * Translate business problems into well-defined machine learning and ... Build and apply classification models for segmentation, fraud detection, churn prediction ...

Photon

AI/ML Data Scientist | Onsite

Dallas, TX · On-site

Key Responsibilities * Translate business problems into well-defined machine learning and ... Build and apply classification models for segmentation, fraud detection, churn prediction ...

Fidelity Investments

Senior Data Scientist

Westlake, TX · On-site

... detection. The successful candidate must be comfortable operating in a fast-paced and sometimes ... Strong technical foundation in machine learning and statistical modeling, with deeper experience in ...

Fidelity Investments

Senior Data Scientist

Westlake, TX · On-site

... detection. The successful candidate must be comfortable operating in a fast-paced and sometimes ... Strong technical foundation in machine learning and statistical modeling, with deeper experience in ...

Waabi

Senior / Staff Perception Engineer

Dallas, TX · On-site +1

$158K - $269K/yr

... machine learning features/models into production. - Experience driving projects on 3D detection, tracking of traffic agents and/or semantic understanding of various traffic scenes. - Passion for ...

Waabi

Senior / Staff Perception Engineer

Dallas, TX · On-site

$158K - $269K/yr

... machine learning features/models into production. - Experience driving projects on 3D detection, tracking of traffic agents and/or semantic understanding of various traffic scenes. - Passion for ...

Waabi

Senior / Staff Perception Engineer

Dallas, TX · On-site

$158K - $269K/yr

... machine learning features/models into production. - Experience driving projects on 3D detection, tracking of traffic agents and/or semantic understanding of various traffic scenes. - Passion for ...

Caterpillar

Principal Perception Architect

Irving, TX · On-site

$159K - $258K/yr

... object detection, semantic understanding, fusion, tracking, 3D mapping, and safety work together as one system. * Own perception-side alignment with Robotics, Edge Platform, Simulation, Machine ...

Addison Group

Lead Engineer

Dallas, TX · Remote

$104K - $138K/yr

NET, Java, or other object-oriented technologies. * Lead the technical design of AI and machine learning solutions for use cases such as document classification, information extraction, image ...

Northern Base

Senior AI ML Engineer

Irving, TX · On-site

$100K - $137K/yr

... machine learning, AI model evaluation, and agentic evaluation frameworks ✔ Experience with MLOps, model monitoring, drift detection, retraining, and AI lifecycle management (Preferred) ✔ ...

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All JobsMachine Learning Object Detection JobsMachine Learning Object Detection Jobs in Northlake, TX

Machine Learning Object Detection information

See Northlake, TX salary details

$29.2K

$119.4K

$179.4K

How much do machine learning object detection jobs pay per year?

As of Sep 15, 2026, the average yearly pay for machine learning object detection in Northlake, TX is $119,389.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $143,700.00 per year, depending on experience, location, and employer.

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 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 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 cities near Northlake, TX are hiring for Machine Learning Object Detection jobs?

Cities near Northlake, TX with the most Machine Learning Object Detection job openings:

Machine Learning Object Detection jobs near you
Infographic showing various Machine Learning Object Detection job openings in Northlake, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $119,389 per year, or $57.4 per hour.

Staff Software Engineer, Perception (R5421)

Dallas, TX • On-site

Shield AI
Software Development • 11 - 50 employees
Learn more about Shield AIexternal

$195K - $292K/yr

Full-time

Re-posted 19 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.
 
In this role, you'll lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems. You'll own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization.
What You'll Do:

Model Development - Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. 

Data Pipelines & Model Training - Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. 

Model Deployment & Optimization - Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. 

Perception & Autonomy Applications - Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. 

Research-to-Production - Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. 

Cross-functional Collaboration - Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. 

Model Evaluation & Validation - Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. 

Continuous Improvement - Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. 

Required Qualifications:

  • Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or 4 years with a PhD; or equivalent work experience.

  • Expertise of machine learning fundamentals. 

  • Experience training an deploying ML models for computer vision in a production setting. 

  • Strong understanding of 3D vision problems/algorithms. 

  • Experience with machine learning frameworks such as PyTorch and TensorFlow. 

  • Demonstrated expertise in deploying models using TensorRT and ONNX. 

  • Proficiency in C++ and Python. 

  • Strong analytical and problem-solving skills, with the ability to translate research into practical applications. 

  • Ability to obtain a SECRET clearance 
Preferred Qualifications:

  • Experience with developing autonomous systems for defense customers. 

  • Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.  

  • Contributions to open-source projects in machine learning or computer vision. 

  • Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

$195,200 - $292,800 a year
#LI-DS-1
#LD

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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