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Remote Python Llm Jobs in California (NOW HIRING)

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Principal Software Engineer (Python)

Irvine, CA · On-site +1

$144K - $194K/yr

The hybrid-remote Principal Software Development Engineer leads the design, development, and ... Model Optimization (LLM & SLM): Partner with the Data Science team to architect intelligent routing ...

David Joseph & Company

AI Engineer

San Francisco, CA · Remote

$150K - $250K/yr

AI Engineer Type: Full-time | Remote (US) -- San Francisco preferred Compensation: $150K - $250K ... Python, TypeScript, LLM tooling (LangGraph, Mastra, Agents SDK), LLM evals + applied GenAI What We ...

MatX

Runtime Engineer

Mountain View, CA · On-site +1

$175K - $362K/yr

Build Python bindings via PyO3, with a C-ABI shim as the alternative integration path for ... Build the LLM inference serving stack - paged KV cache, continuous batching, request scheduling ...

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Remote Python Llm information

What remote jobs can you get with Python?

Remote Python jobs include roles such as software developer, data analyst, machine learning engineer, and automation engineer. These positions often require proficiency in Python programming, familiarity with frameworks like Django or Flask, and experience with cloud platforms or version control tools. Many of these jobs offer flexible schedules and can be performed from any location with internet access.

Will AI replace Python devs?

Remote Python developers are unlikely to be fully replaced by AI, as their role involves complex problem-solving, coding, and adapting to new requirements that AI tools currently cannot fully replicate. AI can assist by automating repetitive tasks and improving productivity, but human oversight and expertise remain essential for software development. Staying updated with new tools and skills can help Python developers remain valuable in an evolving tech environment.

What is a Remote Python LLM job?

A Remote Python LLM job typically involves working with large language models (LLMs) like GPT or similar AI technologies using the Python programming language, while operating remotely. Professionals in this role develop, fine-tune, and deploy machine learning models, especially those focused on natural language processing (NLP) tasks. Responsibilities may include building Python applications that integrate with LLMs, data preprocessing, and collaborating with teams across different locations. The remote aspect allows for flexible work arrangements and access to global opportunities.

What are some common collaboration methods used by Remote Python LLM engineers when working with cross-functional teams?

Remote Python LLM engineers frequently collaborate with data scientists, product managers, and other developers through virtual meetings, code reviews, and shared documentation platforms. Tools like Slack, GitHub, and Jira are often used to ensure smooth communication and project tracking, despite working across different time zones. Regular stand-ups and sprint planning sessions help align objectives and keep everyone updated on progress. Proactive communication and clear documentation are key to overcoming the challenges of remote, distributed teamwork in this role.

Is Python used in LLM?

Yes, Python is widely used in developing large language models (LLMs) and is a key skill for remote Python LLM roles. It provides extensive libraries and frameworks such as TensorFlow and PyTorch that facilitate model training, fine-tuning, and deployment.

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

To thrive as a Remote Python LLM Engineer, you need strong proficiency in Python programming, experience with large language models (LLMs), and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems like Git is typically required. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote collaboration and troubleshooting. These skills ensure you can develop, deploy, and maintain advanced language models efficiently while working independently in distributed teams.

Which LLM is good for Python coding?

For a Remote Python Llm role, models like OpenAI's GPT-4 and GPT-3.4 are widely used for Python coding due to their strong language understanding and code generation capabilities. Additionally, open-source models such as Meta's Llama 2 and EleutherAI's GPT-NeoX can be fine-tuned for specific coding tasks, making them suitable options for development environments requiring customization. Proficiency in integrating these models with APIs and understanding their limitations is essential for effective Python coding assistance.
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Remote Python Llm jobs near you
Principal Software Engineer - Large-Scale LLM Memory and Storage Systems

Principal Software Engineer - Large-Scale LLM Memory and Storage Systems

Nvidia

Santa Clara, CA • On-site, Remote

$158K - $212K/yr

Full-time

Posted 13 days ago

Job description

NVIDIA Dynamo is a high-throughput, low-latency inference framework for serving generative AI and reasoning models across multi-node distributed environments. Built in Rust for performance and Python for extensibility, Dynamo orchestrates GPU shards, routes requests, and manages shared KV cache across heterogeneous clusters so that many accelerators feel like a single system at datacenter scale. As large language models rapidly outgrow the memory and compute budget of any single GPU, this platform enables efficient, resilient deployment of cutting-edge LLM workloads.


We are seeking a Principal Systems Engineer to define the vision and roadmap for memory management of large-scale LLM and storage systems.


What you'll be doing:

  • Design and evolve a unified memory layer that spans GPU memory, pinned host memory, RDMA-accessible memory, SSD tiers, and remote file/object/cloud storage to support large-scale LLM inference.

  • Architect and implement deep integrations with leading LLM serving engines (such as vLLM, SGLang, TensorRT-LLM), with a focus on KV-cache offload, reuse, and remote sharing across heterogeneous and disaggregated clusters.

  • Co-design interfaces and protocols that enable disaggregated prefill, peer-to-peer KV-cache sharing, and multi-tier KV-cache storage (GPU, CPU, local disk, and remote memory) for high-throughput, low-latency inference.

  • Partner closely with GPU architecture, networking, and platform teams to exploit GPUDirect, RDMA, NVLink, and similar technologies for low-latency KV-cache access and sharing across heterogeneous accelerators and memory pools.

  • Mentor senior and junior engineers, set technical direction for memory and storage subsystems, and represent the team in internal reviews and external forums (open source, conferences, and customer-facing technical deep dives).

What we need to see:

  • Masters or PhD or equivalent experience

  • 15+ years of experience building large-scale distributed systems, high-performance storage, or ML systems infrastructure in C/C++ and Python, with a track record of delivering production services.

  • Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and experience designing systems that span multiple tiers for performance and cost efficiency.

  • Distributed caching or key-value systems, especially designs optimized for low latency and high concurrency.

  • Hands-on experience with networked I/O and RDMA/NVMe-oF/NVLink-style technologies, and familiarity with concepts like disaggregated and aggregated deployments for AI clusters.

  • Strong skills in profiling and optimizing systems across CPU, GPU, memory, and network, using metrics to drive architectural decisions and validate improvements in TTFT and throughput.

  • Excellent communication skills and prior experience leading cross-functional efforts with research, product, and customer teams.

Ways to stand out from the crowd:

  • Prior contributions to open-source LLM serving or systems projects focused on KV-cache optimization, compression, streaming, or reuse.

  • Experience designing unified memory or storage layers that expose a single logical KV or object model across GPU, host, SSD, and cloud tiers, especially in enterprise or hyperscale environments.

  • Publications or patents in areas such as LLM systems, memory-disaggregated architectures, RDMA/NVLink-based data planes, or KV-cache/CDN-like systems for ML.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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