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Machine Learning Object Detection Jobs in Utah (NOW HIRING)

... and machine learning to detect and respond to advanced threats. * Comprehensive understanding of the network threat lifecycle, attack vectors, and methods of exploitation, including intrusion set ...

Lead, Software Engineer - FPGA

Salt Lake City, UT · On-site

$124K - $160K/yr

Signal detection, classification, and identification * Radar systems and signal processing ... Machine learning * FPGA verification using simulation and unit testing * Experience developing in ...

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with C++, C or other object-oriented language. * Experience with hardware-software ...

Software Engineer II

Provo, UT · On-site

$92K - $126K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with C, C++, or other object-oriented language. * Experience with hardware-software ...

Showing results 41-60

Machine Learning Object Detection information

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 are popular job titles related to Machine Learning Object Detection jobs in Utah?

For Machine Learning Object Detection jobs in Utah, the most frequently searched job titles are:

What cities in Utah are hiring for Machine Learning Object Detection jobs?

Cities in Utah with the most Machine Learning Object Detection job openings:

Engineering- Salt Lake City - Associate, Systems Engineering - 10442648

Goldman Sachs

Salt Lake City, UT • On-site

Full-time

Posted 9 days ago


Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

47th of 171 rated banks


Job description

Job Duties: Associate, Systems Engineering with Goldman Sachs Services LLC in Salt Lake City, Utah. Develop expertise across all Engineering, including storage, operating systems, databases, messaging, market data, exchange/clearing interface, and software languages. Contribute to design and development of the firm's Listed Clearing software and data infrastructure by identifying internal hardware and implementing and supporting public and private cloud-based solutions to provide on-demand scaling of the firm's applications. Apply data interrogation and analysis, Generative AI, and machine learning techniques to identify and react to problems in the firm's infrastructure and platforms. Identify, analyze, and resolve application issues by creating "Skills" which can be used by AI agents for repetitive error resolutions and minimizing operational errors. Develop Monitoring and Observability solutions to track and manage application health and support application service performance by identifying bottlenecks in the systems. Monitor, mitigate, and prevent risk in the production environment by enforcing change management processes. Review and assess production incidents and communicate with users, applications owners, vendors, and internal and external stakeholders. Develop sustainable systems and services through automation, performance tuning of application and database code. Improve exchange and clearing house processing throughput for Listed Derivatives flow to meet exponential business demands. Plan and build Disaster recovery capabilities in enterprise applications.

Job Requirements: Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Information Systems/Technology, or related field and three (3) years of experience in job offered or related role OR Master's degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Information Systems/Technology, or related field and one (1) year of experience in job offered or related role. Prior work experience must include three (3) years with Bachelor's OR one (1) year with Master's with the following: performance tuning and troubleshooting application and database issues utilizing SQL performance tuning and diagnosing potential performance issues by analyzing query execution plans, java code debugging, or log analysis; software development using UNIX operating system, Shell scripting, or Object-Oriented (OO) languages like Java; supporting production systems utilizing Database technologies including DB2 or Sybase ASE, and messaging technologies including MQ, EMS, or Object-Oriented (OO) languages like Java; working with the full Software Development Life Cycle (SDLC) including requirements gathering, design, prioritization, coding testing, release, and support using tools like Github; and executing periodic disaster recovery testing to ensure business continuity.

The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.


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About Goldman Sachs

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At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869