Turing

Remote Linux developer jobs with top U.S. companies

At Turing, we are looking for talented remote Linux developers who can design, implement and monitor the applications’ infrastructure. If you are passionate about building and developing solutions in Linux, here’s your chance to accelerate your career by working with top U.S companies.

Find remote software jobs with hundreds of Turing clients

Job description

Job responsibilities

  • Work across multiple Linux kernel versions
  • Design and develop reporting and infrastructure monitoring tools
  • Develop test automation frameworks
  • Define software requirements and functional specifications
  • Build and maintain configuration management solutions
  • Develop support for new interfaces
  • Perform regular technical coordination

Minimum requirements

  • Bachelor’s/Master’s degree in computer science (or equivalent experience)
  • 3+ years experience in developing and maintaining Linux file system (rare exceptions for super talented devs)
  • Working knowledge of basic Linux tools, such as bash scripts, make/cmake, etc.
  • Familiarity with Linux scripting languages such as Shell scripts, Perl, TCL, etc.
  • Capability to work full-time (40 hours/week) and overlap 4+hours with U.S. time zones
  • Ability to collaborate with internal and external stakeholders

Preferred skills

  • Proficient in C programming and versioning tools like Git
  • Excellent problem-solving skills and attention to detail
  • In-depth knowledge of system administration and Red Hat Linux
  • Knowledge of Linux security patching, SAN, NAS, and networking
  • Fluency in English and effective collaboration skills

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1Elite US Jobs

Turing’s developers earn better than market pay in most countries, working with top US companies.
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2Career Growth

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How to become a Linux developer ?

Linux developers are among the most in-demand professionals in the tech market today, and that’s why the competition for top jobs remains fierce. Linux is one of the most widely used operating systems and it is constantly growing, especially in the business environment as it has a large community to back it up in case of errors. As an OS, it is open-source and primarily developed for computers, servers, mainframes, mobile devices, and embedded devices.

Linux developers are responsible for developing, documenting, and debugging computer programs for the Linux OS and related software applications. Their responsibilities are generally similar to those of software developers and may include using C ++, Python, or any other programming language to write code or instructions that the device can understand.

Given the increasing popularity of the Linux OS and the increasing market demand for Linux developers, one might wonder how to become a Linux developer. In this section, we will guide you through the structured approach, professional knowledge, and skills required to become a Linux developer.

What is the scope of Linux development?

Digital devices determine our daily life. Be it a laptop, a smartphone, or a PC, our daily life can no longer be imagined without them. The operating system manages these devices. There are different types of operating systems and Linux is most renowned among them.

Operating systems like Android are based on Linux as it is an open-source operating system and is used by almost every big company around the world. This includes industry giants like Twitter, Google, Facebook, IBM, Amazon, McDonald's, and many more.

What are the roles and responsibilities of a Linux developer?

Linux developers are technical professionals who specialize in maintaining and developing Linux infrastructure technology using Linux kernel. They maintain best practices on managing systems and services across multiple roles, including:

  • Troubleshoot, analyze, and log information about performance exceptions
  • Proactively monitor system performance and plan capacity
  • Manage, coordinate, and deploy software updates, patches, hotfixes to servers, workstations, and network hardware
  • Create and modify scripts or applications to perform tasks
  • Input to provide ways to improve the stability, security, efficiency, and scalability of the environment
  • Collaborate with other teams and team members to develop automation strategies and deployment processes

How to become a Linux developer?

The following are some pointers you need to follow to land remote Linux developer jobs.

  • If you are an average learner, you can use YouTube to learn the concepts. It offers free access to all web development courses, although they are not in-depth.
  • If you're a slow learner, you can go to Udemy and can go through all of the free web development courses available.
  • You can go to the website of the particular tech stack you wish to study and read through the entire documentation available. There are other institutions, both online and offline, that have sprung up to meet this widespread need for courses. Be proactive to leverage them as well.
  • Drafting an insightful remote Linux developer resume can also help to be considered for top opportunities.

Now, let's look at the skills and methods you'll need to master to become a successful Linux developer.

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Skills required to become a Linux developer

Linux development is not at all easy as it requires a lot of patience and hard work. You’re required to have deep knowledge of domains and OS to get a high-paying Linux developer job. Some of the skills required to become a Linux Developer include:

1. C programming

You must first learn C programming as most parts of the Linux kernel are written in C and some parts are written in assembly language. If you want to contribute to very low parts of the kernel, you can also learn assembly language. But in the early stages, learning the C language is a must. Also note that the Linux kernel does not depend on the standard C library, so some parts of the C library are not supported.

2. Data structure and algorithm

To become a Linux kernel developer, you must have a basic understanding of data structures and algorithms. An algorithm is usually a step-by-step approach to solving a specific problem, while data structures are concerned with how the data is organized. These two concepts help developers to solve the problem utilizing less memory and time. Understanding data structures and algorithm concepts will help you find the optimal solution for a specific problem. Meanwhile, you can search for various online and offline resources to master data structures and algorithm concepts.

3. Operating system

After learning how to program, you must become familiar with the operating system and its core concept. You can refer to books to learn more about operating systems, or you can opt for an online course.

4. Linux kernel

Now is the time to get acquainted with the internals of the Linux kernel. To learn more about the Linux kernel, it is recommended that you read Kinuc kernel documentation as learning kernel is very crucial to becoming a Linux developer

5. Competitive programming

To master algorithms and data structures, you can perform competitive programming. Now the question arises, what is competitive programming? Competitive programming is about solving problems in a short time and with limited storage space. It teaches you to think. It also shows you how to solve a problem in a limited period of time. In kernel development, you’ll need to solve the problems every day without affecting memory and the speed of code. That’s why competitive programming is very beneficial for a kernel developer.

6. Version control

Every project, whether in Linux or any other kernel, goes through tons of changes and versions during its operational phase. Version control can help you keep track of even the smallest changes with full traceability. This becomes increasingly important when you collaborate with other developers on a project. There are some of the best version control tools out there like Git, Mercurial, Apache Subversion, and many more, but Git is the most popular of all.

7. Analytical skills

Not just Linux, but any developer working with any kernel must have strong analytical skills with strong experience and a good understanding of the algorithms that drive things. One of the many skills of a good developer is his ability to write clear, non-redundant, and extremely optimized code with the correct logic. Once you get started, you should be able to hone your analytical skills as they become more relevant and important for working on operating systems, where you constantly process, analyze, and visualize the OS.

Interested in remote Linux developer jobs?

Become a Turing developer!

Apply now

How to get remote Linux developer jobs?

Linux is the core of operating systems. With security and data breach threats increasing day by day, Linux operating systems are given preference over others, hence the demand for Linux developers is drastically increasing. Apart from operating systems, Linux developers can benefit organizations in multiple ways by utilizing a variety of Linux distros for software operations. However, to work on multiple projects they have to reach that proficient level of Linux development. In this regard, there are two primary factors that developers need to focus on to achieve this level of proficiency in the Linux kernel, its distros, and effective implementation of Linux in multiple operating systems. So make sure to get effective Linux development knowledge that can pass you through any development challenge!

Working remote necessitates being skilled and attractive enough for employers to hire you despite the distance or time difference. To land successful remote Linux developer jobs, you need to stay on top of your technical skills and establish a productive work routine.

Turing offers the best remote Linux developer jobs that will suit your career as an engineer. Grow quickly by working on challenging technical and business programs using the latest technology. Join a network of the world's best developers and land long-term full-time jobs for remote developers with better compensation and career development.

Why become a Linux developer at Turing?

Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top US firms from the comfort of your home.

Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their Linux developers?

At Turing, Linux developers can work according to their own decided rate. However, Turing recommends/suggests you a salary where we know we can find you a stable and profitable long-term opportunity. Our recommendations are based on our evaluation of market conditions, individual skills, and the demand we see from our clients.

Frequently Asked Questions

Linux developer salaries can depend on a number of different factors like experience seniority, related tech stack, and also location. If you’re looking to work as a remote Linux developer you can easily expect a package of anything between 10,000 to 50,000 dollars annually from the comfort of your home. To find the best opportunities with US-based organizations, Turing.com is one of the best platforms to start working with US-based elite companies.

Linux is used to create a range of applications, interfaces programs, and also software. The codes are mostly deployed to PCs, real-time programs, and systems to develop high-end and scalable digital products and tools.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

The pay scale of remote Linux kernel developers can range between 10,000 to 50,000 dollars annually. It can vary based on different factors - experience and seniority level, related skillset, and also location. To find the best remote Linux developer jobs, you can sign up to Turing.com and check out the best opportunities.

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

Here is a list of some of the best Linux platforms for programming - Debian GNU/Linux, Ubuntu, openSUSE, Fedora, Pop!_OS, Arch Linux, Solus OS, and Manjaro Linux.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

View more FAQs

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Leadership

In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

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briefcase
Principal AI Engineer - US NYC

Principal AI Engineer

Location: US(NYC)- 3(WFO)

Employment Type: Full Time (Overlapping EST)

Experience Level: Staff/Principal (8–14 years)


About the Role

Turing is hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients. This is a hands-on engineering role focused on designing and shipping autonomous, tool-calling AI systems — agents that reason over enterprise context, invoke real systems through secure interfaces, and operate reliably at scale under strict latency, cost, and governance constraints.

You will own these systems end to end: the data pipelines feeding them, the backend services around them, the agent orchestration layer, the evaluation harness that keeps them honest, and the cloud infrastructure they run on. We are looking for engineers with genuine software engineering and data science depth who have taken agentic systems all the way to production.

What We're Looking For

Engineering foundation

  • 8–14 years of software engineering experience, with strong hands-on large-scale Python
  • Working depth in at least one systems or backend language — Go, Rust, Java, or C/C++ — and the judgment to know when to reach for it
  • Strong data structures and algorithms.
  • Strong understanding of APIs, microservices, and system design
  • Hands-on experience building and operating data pipelines and production-grade distributed systems.

Agentic AI and LLMs

  • 2+ years of hands-on LLM engineering, with at least couple agentic system you designed and took to production
  • Production experience with agent frameworks — LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent — and the fluency to move between them as the ecosystem evolves
  • Experience building MCP (Model Context Protocol) servers and tool-calling interfaces
  • RAG from first principles: chunking strategy, embeddings, vector and hybrid retrieval, reranking, and response validation
  • Strong experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc. or cloud equivalents)
  • Design of guardrails and reliability patterns — validators, policy checks, self-correction loops, deterministic fallbacks, circuit breakers, and rollback paths

Optimization

  • Deep familiarity with token optimization and context-window management — context shaping, pruning, and compaction
  • Latency and cost optimization through caching, model routing, batching, streaming, and parallel tool calls
  • Performance testing and tuning systems against defined SLOs

Evaluation

  • Experience building evaluation frameworks for LLM systems — offline eval sets, continuous online evaluation, and regression detection
  • Instrumentation and traceability suitable for regulated enterprise environments using tools like LangSmith, Langfuse, etc.

Cloud

  • Hands-on AWS: containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift) and orchestration (Step Functions); Azure or GCP equivalents also valued
  • Familiarity with CI/CD pipelines and DevOps practices
  • Infrastructure as code with Terraform or CloudFormation, and mature CI/CD practice

Working traits

  • Strong analytical problem-solving with a bias to ownership and urgency
  • Clear cross-team communication, working directly with client stakeholders to translate business problems into technical roadmaps
  • Able to work productively in ambiguity from system-level documentation and ramp quickly in unfamiliar codebases

Good to Have

  • Experience with managed AI platforms — Amazon Bedrock, Vertex AI, Azure AI — paired with fluency in the underlying fundamentals

Roles & Responsibilities

  • Design and build agentic systems: Lead the architecture and implementation of tool-calling agents that combine retrieval, structured reasoning, and secure action execution with least-privilege access.
  • Productionize LLM applications: Build retrieval pipelines, prompt synthesis, response validation, and self-correction loops, backed by rigorous evaluation.
  • Own the full stack: Deliver the data pipelines, backend services, distributed compute, and orchestration layer that agentic systems depend on — not only the model invocation.
  • Engineer for reliability and governance: Build validator models, adversarial test suites, and policy checks; enforce deterministic fallbacks and rollback strategies; instrument continuous evaluation.
  • Optimize for cost and latency: Drive measurable improvements in token efficiency, response time, and unit economics against defined SLOs.
  • Codebase ownership: Build, maintain, and review high-quality Python and SQL, with an emphasis on reusable components, scalability, and performance.
  • Cloud integration: Deploy AI applications on AWS, Azure, or GCP with optimized resource usage and robust CI/CD.
  • Cross-functional collaboration: Partner with product owners, data scientists, and business SMEs to define requirements and deliver impactful AI products.
  • Mentoring and technical leadership: Set engineering standards and share knowledge across the team, raising the bar on AI and software engineering practice.
Finance
10K+ employees
PythonGoRust+ 4
briefcase
Lead Edge AI & Computer Vision Engineer

Lead Edge AI & Computer Vision Engineer

  • Location: USA [with regular on-site travel required to client site]
  • Target Start Date: 1 Sep
  • Time Commitment: 8 weeks full-time
  • Experience Level: 12–15+ Years

Core Objective: Architect, benchmark, and optimize an end-to-end computer vision and low-latency execution pipeline—combining spatial geometric math with low-level C++/CUDA acceleration directly on NVIDIA Jetson embedded edge hardware (Orin NX / AGX Orin) to achieve sub-10 ms processing latency.

Key Responsibilities

  1. Model Selection & Spatial Math: Evaluate real-time detection topologies (e.g. YOLO) at 100+ FPS and build 2D perspective homography unwarping, lens undistortion, and spatial algorithms to convert pixel coordinates into physical millimeter units within tight error bounds (millimeter level accuracy).
  2. TensorRT INT8 Acceleration: Execute Post-Training Quantization to compile PyTorch/ONNX models into high-throughput TensorRT INT8/FP16 engines on Jetson Orin hardware without accuracy degradation.
  3. Zero-Copy Memory Architecture:  Engineer zero-copy memory pipelines using NVIDIA Memory Management and DMA transfers to eliminate bottlenecks.
  4. Compiled C++ Execution & I/O: Build compiled C++17 execution frameworks with multi-threaded lock-free ring buffers and non-blocking asynchronous socket communication.
  5. Nsight Profiling & Roadmapping: Instrument stage-by-stage pipeline latency using NVIDIA Nsight Systems/NVTX markers to bound tail latency, author feasibility reports, and design technical roadmaps.

Key Qualifications & Experience

  1. Full-Stack Edge AI Experience: 12–15+ years of experience bridging real-time computer vision algorithm design, spatial geometry, and low-level C++/CUDA execution on embedded edge hardware.
  2. NVIDIA Jetson Ecosystem: Deep expertise in Jetson embedded platforms (Orin NX, AGX Orin, L4T, power profiles, core pinning) and a proven track record compiling/tuning TensorRT FP16/INT8 engines via PTQ/QAT.
  3. Optical & Spatial Geometry: Expertise in 2D/3D camera calibration, perspective homography transformations, lens distortion modeling, and millimeter sizing math in industrial settings.
  4. Low-Latency Systems Engineering: Expertise in zero-copy shared memory, DMA frame buffers, lock-free queues, custom CUDA plugins, and microsecond profiling via Nsight Systems and NVTX markers.
  5. Tooling & Industrial I/O: Proficiency in C++17, Python, PyTorch, OpenCV, CUDA, non-blocking asynchronous sockets (UDP, PLC integration), and building automated dataset benchmarking harnesses.
Manufacturing
10K+ employees
C++CUDANVIDIA Omniverse+ 5
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