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Remote Linux Kernel Developer Jobs in Arizona (NOW HIRING)

Motorola

Senior DevOps Engineer (US REMOTE)

Phoenix, AZ · Remote

$140K - $170K/yr

Manage developer tooling * Ensure compliance with regulatory, compliance and security frameworks ... Experience with Linux including scripting (Bash) Preferred Skills: * Experience with AI/machine ...

Epiq

Associate IT DevOps Engineer

Phoenix, AZ · Remote

$80K - $95K/yr

Experience with Windows Server, Ubuntu Linux, Red Hat Linux * Scripting experience in Python or ... VMware VCP or related certifications #LI-KS1 #LI-Remote The Compensation range for this role is $80 ...

360 IT Professionals

Sr Software Engineer

Chandler, AZ · Remote

$120K - $159K/yr

... ; DevOps experience with clusters, sharding, and technologies such as Ansible, Lambdas , etc ... Experience with software lifecycle and development tools such as Linux/JVM internals, Jersey, Jetty ...

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Remote Linux Kernel Developer information

What are Remote Linux Kernel Developers?

Remote Linux Kernel Developers are software engineers who specialize in developing, maintaining, and improving the Linux kernel while working from a location outside of a traditional office. Their work often involves writing, debugging, and optimizing kernel code, collaborating with open-source communities, and ensuring system stability and performance. These developers typically possess deep knowledge of C programming, operating system concepts, and hardware interfaces. Working remotely, they use various collaboration tools to contribute to projects and communicate with team members globally.

What are the key skills and qualifications needed to thrive as a Remote Linux Kernel Developer, and why are they important?

To thrive as a Remote Linux Kernel Developer, you need a deep understanding of C programming, operating system concepts, and kernel architecture, often supported by a degree in computer science or related experience. Familiarity with Git, Linux kernel build systems, debugging tools like GDB, and contributing to open-source repositories is typically required. Strong problem-solving abilities, clear written communication, and self-motivation are essential soft skills for remote collaboration and troubleshooting. These skills ensure the ability to develop, maintain, and optimize kernel code effectively while working independently within distributed teams.

What are some common challenges faced by remote Linux Kernel Developers when collaborating with distributed teams?

Remote Linux Kernel Developers often work with globally distributed teams, which can present challenges such as coordinating across time zones, maintaining clear communication, and ensuring code consistency. Effective collaboration typically relies on asynchronous communication tools, thorough code documentation, and participation in regular virtual meetings or code reviews. Developing strong self-management skills and familiarity with collaborative platforms like Git and mailing lists is essential to staying aligned with the team's goals and maintaining productivity.
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Remote Linux Kernel Developer jobs near you

ML Infrastructure Engineer

Bright Vision Technologies

Scottsdale, AZ • On-site, Remote

$100K - $150K/yr

Full-time

Posted 3 days ago

Job description

ML Infrastructure Engineer - Remote 
 
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. 
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. 
 
Job Title: ML Infrastructure Engineer
Location: 100% Remote (U.S.) 
Position Type: Full-time, Direct W2 
Salary Range: $100,000–$150,000 Annually 
Experience Required: 6+ years 
 
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. 
 
Job Summary 
We are seeking an AI Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control. The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work. 
Key Responsibilities 
  • Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations. 
  • Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams. 
  • Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering. 
  • Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate. 
  • Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication. 
  • Build observability for AI workloads including utilization, throughput, training stability, and failure-mode analytics. 
  • Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scale. 
  • Drive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizing. 
  • Develop developer tooling and paved-road workflows that let researchers launch experiments safely and efficiently. 
  • Partner with research and applied ML teams to plan capacity for upcoming training runs. 
  • Implement security controls, isolation, and access management for multi-tenant AI infrastructure. 
  • Drive automation across cluster provisioning, lifecycle management, and configuration enforcement. 
  • Maintain runbooks, capacity dashboards, and operational documentation for the AI platform. 
  • Stay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling. 
Required Qualifications 
  • Bachelor’s or Master’s degree in Computer Science or a related field. 
  • Six or more years of experience in infrastructure, platform, or HPC engineering. 
  • Hands-on experience operating GPU clusters or large-scale ML training infrastructure. 
  • Strong proficiency in Python and at least one systems language such as Go or C++. 
  • Deep understanding of distributed training, accelerator architectures, and collective communication. 
  • Experience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloads. 
  • Strong understanding of Linux internals, networking, and high-performance storage. 
  • Experience with at least one major cloud provider’s ML infrastructure offerings. 
  • Strong software engineering practices including testing, CI/CD, and code review. 
  • Excellent communication and cross-functional collaboration skills. 
Preferred Qualifications 
  • Experience operating InfiniBand or RDMA networking at scale. 
  • Contributions to open-source ML infrastructure projects. 
  • Familiarity with custom orchestrators or research-grade training stacks. 
  • Exposure to frontier model training operations. 
  • Experience with FinOps for AI workloads. 
How to Apply 
Would you like to know more about this opportunity? For immediate consideration, please send your resume to Jenny@bvteck.com or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
 

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees\' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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