Llm Engineer Jobs
Llm Engineer jobs are open across AI research labs, enterprise software, fintech, and healthtech, from junior to staff and principal levels, with specializations in retrieval-augmented generation, fine-tuning, and prompt engineering. Find a role that fits from the openings below and apply directly.
Find Llm Engineer JobsStudent or new grad? View llm engineer internships →Overview
Showing 5 of 82+ Llm Engineer jobs
The Microsoft AI Frameworks team develops the software and systems that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. We work across model architectures, frameworks, compilers, runtimes, libraries, and hardware platforms—including NVIDIA and AMD GPUs and Microsoft silicon.
We are seeking hands-on Senior and/or Principal Software Engineers to deliver state-of-the-art performance for an LLM serving stack. You will optimize GPU kernels, compilers, runtimes, and distributed inference systems to improve latency, throughput, reliability, and hardware efficiency.
Successful candidates combine strong systems engineering, deep performance expertise, disciplined measurement, and effective cross-team collaboration.
As a Senior Software Engineer, you will own significant performance improvements across GPU kernels and inference runtime components, carrying optimizations from investigation through production.
As a Principal Software Engineer, you will tackle the most difficult cross-stack performance challenges and create reusable capabilities that advance serving performance across models and hardware generations.
Responsibilities
As a Senior Software Engineer:
Develop and optimize GPU kernels and runtime components for state-of-the-art LLM serving performance.
Profile workloads and improve latency, throughput, and hardware efficiency.
Integrate robust, maintainable optimizations into production serving systems.
Collaborate across model, compiler, infrastructure, and hardware teams.
Use AI-assisted development tools effectively to accelerate the development process.
Contribute to technical reviews, engineering standards, and mentoring.
Embody Microsoft’s culture and values.
As a Principal Software Engineer:
Drive cross-stack optimization across kernels, compilers, runtimes, and distributed serving.
Perform difficult, low-level optimization and resolve critical performance bottlenecks.
Turn performance innovations into reusable production capabilities.
Collaborate across research, infrastructure, and hardware teams to deliver measurable improvements.
Use AI-assisted development tools effectively to accelerate the development process.
Mentor senior engineers and raise engineering standards.
Embody Microsoft’s culture and values.
Qualifications
Required/Minimum Qualifications:
- Bachelor’s Degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C++, or Python, or equivalent experience.
Other Requirements:
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Additional or Preferred Qualifications for Senior Software Engineer
Expertise in GPU or equivalent accelerator programming and kernel optimization.
Familiarity with vLLM, SGLang, or equivalent LLM inference libraries.
Demonstrated cross-team collaboration and technical ownership.
Ability to use AI-assisted development tools efficiently and validate their output.
Additional or Preferred Qualifications for Principal Software Engineer
Deep expertise in GPU or equivalent accelerator compilation pipelines and low-level architecture.
Expertise in LLM training and inference parallelism and acceleration.
Demonstrated ownership of cross-team technical initiatives from strategy through production.
Track record of creating reusable platforms, influencing senior stakeholders, and mentoring technical leaders.
#AIInfra
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
The Microsoft AI Frameworks team develops the software and systems that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. We work across model architectures, frameworks, compilers, runtimes, libraries, and hardware platforms—including NVIDIA and AMD GPUs and Microsoft silicon.
We are seeking hands-on Senior and/or Principal Software Engineers to deliver state-of-the-art performance for an LLM serving stack. You will optimize GPU kernels, compilers, runtimes, and distributed inference systems to improve latency, throughput, reliability, and hardware efficiency.
Successful candidates combine strong systems engineering, deep performance expertise, disciplined measurement, and effective cross-team collaboration.
As a Senior Software Engineer, you will own significant performance improvements across GPU kernels and inference runtime components, carrying optimizations from investigation through production.
As a Principal Software Engineer, you will tackle the most difficult cross-stack performance challenges and create reusable capabilities that advance serving performance across models and hardware generations.
Responsibilities
As a Senior Software Engineer:
Develop and optimize GPU kernels and runtime components for state-of-the-art LLM serving performance.
Profile workloads and improve latency, throughput, and hardware efficiency.
Integrate robust, maintainable optimizations into production serving systems.
Collaborate across model, compiler, infrastructure, and hardware teams.
Use AI-assisted development tools effectively to accelerate the development process.
Contribute to technical reviews, engineering standards, and mentoring.
Embody Microsoft’s culture and values.
As a Principal Software Engineer:
Drive cross-stack optimization across kernels, compilers, runtimes, and distributed serving.
Perform difficult, low-level optimization and resolve critical performance bottlenecks.
Turn performance innovations into reusable production capabilities.
Collaborate across research, infrastructure, and hardware teams to deliver measurable improvements.
Use AI-assisted development tools effectively to accelerate the development process.
Mentor senior engineers and raise engineering standards.
Embody Microsoft’s culture and values.
Qualifications
Required/Minimum Qualifications:
- Bachelor’s Degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C++, or Python, or equivalent experience.
Other Requirements:
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Additional or Preferred Qualifications for Senior Software Engineer
Expertise in GPU or equivalent accelerator programming and kernel optimization.
Familiarity with vLLM, SGLang, or equivalent LLM inference libraries.
Demonstrated cross-team collaboration and technical ownership.
Ability to use AI-assisted development tools efficiently and validate their output.
Additional or Preferred Qualifications for Principal Software Engineer
Deep expertise in GPU or equivalent accelerator compilation pipelines and low-level architecture.
Expertise in LLM training and inference parallelism and acceleration.
Demonstrated ownership of cross-team technical initiatives from strategy through production.
Track record of creating reusable platforms, influencing senior stakeholders, and mentoring technical leaders.
#AIInfra
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
Llm Engineer Jobs by Experience Level
See All 82 Llm Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Llm Engineer JobsLlm Engineer Job Market
Who's Hiring
- TikTok16
- Capital One9
- Apple8
- Molex3
- NVIDIA3
Top Industries Hiring
- Technology & Software11
- Banking & Financial Services5
- Media & Entertainment3
- Electronics & Hardware3
- Automotive2
What Employers Look For
The qualifications that appear most often in llm engineer jobs.
- Proficiency in Python and experience with PyTorch or JAX for model development and fine-tuning
- Hands-on experience with large language models such as GPT, LLaMA, Mistral, or Gemini families
- Familiarity with retrieval-augmented generation pipelines and vector databases like Pinecone or Weaviate
- Experience deploying and optimizing models for production inference using vLLM, TensorRT, or similar tools
- Strong understanding of prompt engineering, context window management, and evaluation frameworks
- Bachelor's or master's degree in computer science, machine learning, or a closely related technical field
Tips for Your Llm Engineer Job Search
Tailor your resume to model infrastructure
Recruiters scanning llm engineer resumes look for specifics: which foundation models you've worked with, whether you've handled inference optimization, and what serving frameworks you've used. Generic 'AI experience' won't stand out. Name the models, the frameworks, and the production scale.
Show evaluation results, not just experiments
Your portfolio should include benchmark results or qualitative eval outputs, not just notebooks. Teams want evidence you can assess model behavior systematically. Even a side project with a documented eval harness signals maturity that most candidates skip.
Filter openings by stack, not just title
LLM engineer job titles vary wildly. Search for 'applied scientist,' 'AI engineer,' and 'foundation model engineer' in addition to the exact title. Then filter by the stack listed in the description to find roles that match your strengths in tools like LangChain, vLLM, or Hugging Face.
Apply early to roles that fit
Migrate Mate lists llm engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for system-design questions on inference
Interviews for llm engineer roles frequently include a system-design round focused on latency, cost, and context management, not just model selection. Practice designing a retrieval-augmented pipeline end-to-end, including chunking strategy, vector store choice, and re-ranking logic.
Negotiate around compute access, not just salary
When you reach the offer stage, GPU access, cloud credits, and research time are negotiable at many AI teams. Ask specifically what compute budget the team works with and whether engineers have discretionary access. These resources affect what you can actually build.
Llm Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most llm engineers?
The companies hiring the most llm engineers right now include TikTok, Capital One, and Apple, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is concentrated at AI-native startups and large technology companies building internal generative AI products.
How many llm engineer jobs are remote?
About 50% of llm engineer openings are fully remote or hybrid as of September 2026, making it one of the more remote-accessible engineering disciplines. Roles focused on prompt engineering, evaluation, and RAG pipeline development tend to be the most remote-friendly, while positions involving on-premises GPU infrastructure or close cross-functional collaboration often require some on-site presence.
How do you become a llm engineer?
Start by building a strong foundation in Python and deep learning fundamentals, then work through the Hugging Face course and experiment with open-source models locally. Build at least one end-to-end project that includes fine-tuning or retrieval-augmented generation, document your evaluation process, and publish the code. Contributing to open-source LLM tooling and writing about your experiments publicly accelerates hiring significantly.
Can you get hired as a llm engineer without direct experience?
Yes, particularly at companies still building their AI teams from scratch. The most effective approach is demonstrating hands-on competence through a public portfolio: a fine-tuned model on Hugging Face, a documented RAG system on GitHub, or a technical write-up of an eval you designed. Hiring managers in this space weight demonstrated ability over credentials because the field is too new for long resumes to exist.
What does the llm engineer interview process look like?
Most processes include a recruiter screen, a technical phone interview covering Python and ML fundamentals, and a take-home or live coding round focused on a practical task like building a retrieval pipeline or evaluating model outputs. Final rounds typically include a system-design interview on inference architecture and a team-fit conversation. Some companies add a research presentation if the role involves novel modeling work.
Where can I find and apply to llm engineer jobs?
You can find and apply to llm engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your experience and stack, then apply directly to each one that fits. Openings are updated regularly, so checking back frequently gives you access to newly posted roles before they fill.
See All 82 Llm Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Llm Engineer Jobs