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Remote Neural Network Engineer Jobs in Utah (NOW HIRING)

Principal Site Reliability Engineer

Lehi, UT · On-site +1

$53.50 - $71/hr

Strong understanding of networking fundamentals: DNS, TLS/PKI, load balancing, and zero-trust ... Competitive compensation, equity, and comprehensive benefits including flexible PTO and remote ...

Remote; Ability to travel up to 25% * Sales motion: Technical consultative selling across net-new ... Networking and Identity: Troubleshooting DNS, proxies, firewalls, VPCs, and NLBs within NIPR/SIPR ...

Remote; Ability to travel up to 25% * Sales motion: Technical consultative selling across net-new ... Networking and Identity: Troubleshooting DNS, proxies, firewalls, VPCs, and NLBs within NIPR/SIPR ...

Senior Mining Engineer

Sandy, UT · On-site +1

$99K - $136K/yr

... to remote locations * Strong network with mining clients is considered a strong asset ... leader in engineering and consultancy across energy and the built environment, helping to unlock ...

Senior Sales Engineer

Draper, UT · Remote

$125K - $140K/yr

SENIOR SOLUTIONS ENGINEER US REMOTE; RALEIGH, NC, DRAPER, UT EGNYTE YOUR CAREER. SPARK YOUR PASSION ... Broad knowledge of SaaS, infrastructure, network (bandwidth/latency impact on CAD), authentication ...

Circle's platform includes the world's largest regulated stablecoin network anchored by USDC ... You have experience managing remote teams * The ability to thrive on a fast pace environment with ...

Senior Backend Engineer - AI Platform

Salt Lake City, UT · On-site +1

$118K - $156K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... network of fueling stations and merchant partners. We provide fleet managers and operators with ...

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Remote Neural Network Engineer information

What is a Remote Neural Network Engineer?

A Remote Neural Network Engineer is a specialized software engineer who designs, develops, and maintains neural network models while working from a remote location. They use deep learning frameworks such as TensorFlow or PyTorch to build algorithms that mimic the human brain for tasks like image recognition, natural language processing, and predictive analytics. These engineers collaborate with teams virtually and leverage cloud computing resources to train and deploy models. The role requires strong programming, mathematical, and analytical skills, as well as experience working in distributed team environments.

What is the difference between Remote Neural Network Engineer vs Data Scientist?

AspectRemote Neural Network EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; experience with neural networks and deep learning frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentRemote, tech companies, AI research labsRemote or on-site, diverse industries including finance, healthcare, tech
Industry UsagePrimarily in AI, machine learning, and deep learning projectsData analysis, predictive modeling, business insights

While both roles involve working with data and machine learning, a Remote Neural Network Engineer specializes in designing and implementing neural network models, often requiring deep learning expertise. A Data Scientist focuses on analyzing data to extract insights, using a broader set of tools including statistical methods and machine learning. The roles overlap in skills but differ in focus and application.

What are the key skills and qualifications needed to thrive as a Remote Neural Network Engineer, and why are they important?

To thrive as a Remote Neural Network Engineer, you need a strong background in computer science, mathematics, and deep learning principles, often supported by a relevant degree and prior experience in AI or machine learning roles. Proficiency in programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms are essential, and certifications in machine learning can be advantageous. Excellent problem-solving skills, self-motivation, and effective remote communication are key soft skills for collaboration and independent work. These skills and qualities ensure the engineer can design, implement, and optimize neural network solutions efficiently while contributing effectively to distributed teams.

How does a Remote Neural Network Engineer typically collaborate with cross-functional teams when working from a distance?

As a Remote Neural Network Engineer, collaboration with cross-functional teams—such as data scientists, software engineers, and product managers—is primarily facilitated through virtual communication platforms and project management tools. Regular video meetings, code reviews, and shared documentation are essential to ensure alignment on project goals and progress. Clear communication and proactive sharing of updates are crucial to overcoming the lack of in-person interaction. Additionally, remote engineers often use collaborative coding environments and version control systems to streamline joint development efforts and maintain code quality.
What are popular job titles related to Remote Neural Network Engineer jobs in Utah? For Remote Neural Network Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Remote Neural Network Engineer jobs? Cities in Utah with the most Remote Neural Network Engineer job openings:
Principal Site Reliability Engineer

Principal Site Reliability Engineer

DigiCert

Lehi, UT • On-site, Remote

$53.50 - $71/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


Job description

Job summary

The Platform Ops team within CloudOps is responsible for the reliability, scalability, and modernization of DigiCert's cloud infrastructure. As a Principle SRE, you will own the intersection of software engineering and operations-driving automation-first practices, reducing toil, and accelerating our cloud transformation across AWS, Azure, and GCP environments.

You will be a technical force multiplier: raising reliability standards across the organization, defining SLOs that matter, and building the internal platforms and tooling that enable product teams to ship with confidence.

What you will do

Reliability Engineering

  • Define, implement, and own SLIs, SLOs, and error budgets for critical platform services
  • Lead blameless post-mortems and drive systemic reliability improvements across the platform
  • Design and implement observability pipelines (metrics, logs, traces) using tools such as Splunk, Prometheus, Grafana, or OpenTelemetry
  • Participate in on-call rotation and serve as an incident commander for P0/P1 events

Cloud Modernization

  • Architect and execute migration strategies from legacy infrastructure to cloud-native patterns (containers, serverless, managed services)
  • Champion adoption of Kubernetes, service mesh, and managed cloud services (EKS, GKE, AKS)
  • Evaluate and introduce emerging cloud technologies that improve availability, cost efficiency, and developer experience
  • Partner with architecture and security teams to embed reliability and compliance into platform design

Automation & Platform Development

  • Build and maintain infrastructure-as-code using Terraform across multi-cloud environments
  • Develop internal tooling, self-service platforms, and golden-path templates that reduce operational burden for development teams
  • Automate operational workflows including provisioning, scaling, patching, and secret rotation
  • Contribute to and maintain CI/CD pipelines (GitHub Actions) to enable safe, frequent deployments

Engineering Leadership

  • Mentor mid-level engineers on SRE principles, distributed systems, and infrastructure best practices
  • Collaborate cross-functionally with product, security, and compliance teams to deliver on platform roadmap commitments
  • Document architectural decisions, runbooks, and platform standards; raise the engineering bar through code and design reviews

What you will have

  • 5+ years of experience in SRE, platform engineering, or infrastructure engineering roles
  • Deep proficiency in at least one major cloud provider (AWS, GCP, or Azure) with working knowledge of multi-cloud environments
  • Strong software engineering skills in Python, Go, or Bash; comfortable writing production-grade automation and tooling
  • Hands-on Kubernetes experience: cluster operations, workload management, networking (CNI/service mesh), and security (RBAC, pod security)
  • Infrastructure-as-code expertise with Terraform or equivalent; experience with GitOps workflows
  • Proven experience designing and operating observability systems and responding to production incidents at scale
  • Strong understanding of networking fundamentals: DNS, TLS/PKI, load balancing, and zero-trust networking concepts

Nice to have

  • Experience in PKI, certificate lifecycle management, or security-adjacent infrastructure
  • Familiarity with compliance frameworks such as SOC 2, FedRAMP, or ISO 27001 in cloud environments
  • Prior experience driving cloud migration or modernization programs at scale
  • Contributions to open-source infrastructure or platform projects
  • AWS/GCP/Azure professional-level certifications (e.g., AWS Solutions Architect Professional, CKA/CKS)

What success looks like 

In your first 90 days, you'll have a deep understanding of our platform's reliability posture, contributed to at least one automation or modernization initiative, and be a trusted voice in incident response. Within a year, you'll have measurably reduced toil, improved SLO attainment across key services, and delivered at least one major platform capability that enables product teams to move faster.

Working at DigiCert CloudOps 

  • Greenfield modernization: we are actively migrating workloads and building new platform capabilities-you'll shape the architecture, not just maintain it
  • Engineering-first culture with a strong bias toward automation, GitOps, and platform thinking
  • Cross-functional visibility: PlatformOps partners directly with product, security, and compliance-your work has organization-wide impact
  • Competitive compensation, equity, and comprehensive benefits including flexible PTO and remote-first flexibility

Benefits

  • Competitive compensation and comprehensive health, dental, and vision coverage 
  • Retirement savings programs with company matching (401(k) or RRSP) 
  • Generous paid time off, including holidays, and vacation 
  • Paid parental leave and family support benefits 
  • Life and disability coverage 
  • Flexible spending and health savings options (where applicable) 
  • Health and wellness support, including gym reimbursement and wellness programs 
  • Employee Assistance Program with 24/7confidential support for employees and families 
  • Education assistance and professional development opportunities 
  • Access to LinkedIn Learning and continuous learning resources 
  • Employee referral bonus program and additional company perks and discounts 
  • Internal rewards and recognition platform (Motivosity) to celebrate and acknowledge project wins, milestone achievements, and the outstanding contributions of our colleagues
  • Business travel insurance and global employee support programs 

To protect candidate information and maintain a secure hiring process, all applications must be submitted through our careers portal. Resumes or CVs sent directly via email will not be reviewed or considered.

DigiCert is an Equal Opportunity employer and is committed to diversity in its workforce. In compliance with applicable federal and state laws, DigiCert prohibits discrimination on the basis of race or ethnicity, religion, color, national origin, sex, age, sexual orientation, gender identity/expression, veteran's status, status as a qualified person with a disability, or genetic information. Individuals from historically underrepresented groups, such as minorities, women, qualified person with disabilities, and protected veterans are strongly encouraged to apply.

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