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Deep Learning Engineer Jobs in Utah (NOW HIRING)

Applied AI Scientist

Salt Lake City, UT

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Collaborate with engineering, product, and data science teams to understand requirements ... Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ...

Applied AI Scientist

Lehi, UT · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Collaborate with engineering, product, and data science teams to understand requirements ... Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine learning (e.g., PyTorch ) and visualization (e.g., TensorBoard ). * Experience in research communities ...

Senior Data Scientist

Lehi, UT · On-site

  • Medical

  • Retirement

  • PTO

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... deep learning) and their practical applications. * Strong understanding of statistical modeling ...

Senior Data Scientist

Lehi, UT

  • Medical

  • Retirement

  • PTO

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... deep learning) and their practical applications. * Strong understanding of statistical modeling ...

Senior Data Scientist

Lehi, UT

  • Medical

  • Retirement

  • PTO

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... deep learning) and their practical applications. * Strong understanding of statistical modeling ...

Senior Data Scientist

Lehi, UT · On-site

$180 - $250/hr

  • Medical

  • Retirement

  • PTO

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... deep learning) and their practical applications. * Strong understanding of statistical modeling ...

Senior Data Scientist

Lehi, UT · On-site

  • Medical

  • Retirement

  • PTO

... continuous learning within the team. * Collaborate with cross-functional teams (engineering ... deep learning) and their practical applications. * Strong understanding of statistical modeling ...

Data science software developer

Murray, UT · On-site +1

$124K - $170K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Senior Data Science Software Engineer (Solventum) 3M Health Care is now Solventum At Solventum, we ... to build world class deep learning models * Integrating AI models into software pipelines

Data science software developer

Murray, UT · On-site +1

$124K - $170K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Senior Data Science Software Engineer (Solventum) 3M Health Care is now Solventum At Solventum, we ... to build world class deep learning models * Integrating AI models into software pipelines

Data science software developer

Murray, UT · On-site

$124K - $170K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Senior Data Science Software Engineer (Solventum) 3M Health Care is now Solventum At Solventum, we ... to build world class deep learning models * Integrating AI models into software pipelines

Showing results 41-60

Deep Learning Engineer information

See Utah salary details

$34.6K

$105.5K

$174.3K

How much do deep learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for deep learning engineer in Utah is $105,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,600.00 and $137,900.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What does a deep learning engineer do?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What skills and qualifications does a deep learning engineer need?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.

What are the most commonly searched types of Deep Learning Engineer jobs in Utah?

The most popular types of Deep Learning Engineer jobs in Utah are:

What cities in Utah are hiring for Deep Learning Engineer jobs?

Cities in Utah with the most Deep Learning Engineer job openings:

Infographic showing various Deep Learning Engineer job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $105,480 per year, or $50.7 per hour.

Applied AI Scientist

Cisco

Salt Lake City, UT

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Cisco Systems rating

8.0

Company rating: 8.0 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

59th of 159 rated electronics manufacturers


Job description

The application window is expected to close on: 07/31/2026

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Meet the Team

Splunk, a Cisco company, is building a safer, more resilient digital world with an endtoend, fullstack platform designed for hybrid, multicloud environments. Join the Foundational Modeling team at Splunk, where we advance the state of AI for highvolume, realtime, multimodal machinegenerated data - including logs, time series, traces, and events! We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco's global engineering capabilities. Our work spans networking, security, observability, and customer experience - designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You'll be part of a culture that values technical excellence, impactdriven innovation, and crossfunctional collaboration - all within a flexible, growthoriented environment!

Your Impact

  • Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series, traces, and event modalities.
  • Develop and enhance distributed training and inference workflows, leveraging data-driven approaches to improve model quality, scalability, and operational efficiency.
  • Collaborate with engineering, product, and data science teams to understand requirements, incorporate stakeholder feedback, and deliver AI/ML solutions that address business and technical needs.
  • Share emerging ideas, technical insights, and best practices with teammates, contributing to technical discussions and helping advance team capabilities and project outcomes.
  • Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations to improve workflows, solve technical challenges, and support the team's roadmap and objectives.
  • Take ownership of assigned projects and deliver high-quality results with urgency, while proactively identifying obstacles, driving resolution of technical issues, and continuously improving development processes.

Minimum Qualifications:

  • Master Degree in Computer Science, or related quantitative field, plus 2+ years of industry research experience.
  • 1+ year of experience in at least one of the following areas: Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE, heterogeneous GNNs, graph transformers), large language modeling for structured and unstructured data, multi-modal fusion of graph, text, log, and time-series data.
  • 2+ years of experience in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
  • 1+ year experience translating research ideas into production systems.

Preferred Qualifications:

  • Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE), spatio-temporal GNNs, heterogeneous graphs (HGNN/Relational GNNs), and knowledge-graph-augmented modeling.
  • Expertise in constructing and operating on large-scale graphs (entity graphs, service dependency graphs, topology graphs, causal graphs, or log-event graphs).
  • Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems, or custom GNN runtimes.
  • Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting anomalies in high-volume operational data.
  • Hands-on experience developing, fine-tuning, or adapting foundation models for domain-specific data such as logs, time-series, graphs, operational telemetry, or enterprise knowledge, including representation learning across structured and unstructured modalities.
  • LargeScale Training & Optimization - Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
  • MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
  • Strong Research Track Record - Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to stateoftheart methods and realworld applications.
Why Cisco?

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:The starting salary range posted for this position is $168,000.00 to $212,400.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco's policies:

  • 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees

  • 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco

  • Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees

  • Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)

  • 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours ofunused sick timecarried forwardfrom one calendar yearto the next

  • Additional paid time away may be requested to deal with critical or emergency issues for family members

  • Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

  • .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

  • 1.5% of incentive target for each 1% of attainment between 50% and 75%;

  • 1% of incentive target for each 1% of attainment between 75% and 100%; and

  • Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$184,000.00 - $274,600.00

Non-Metro New York state & Washington state:

$168,000.00 - $244,300.00

* For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.


What Cisco Systems employees say

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Hours and flexibility

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About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

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