ML Systems, LLM Post-Training
- Pay
- $150,000 per year
- Location
- San Jose, CA
- Listed
- 5 days ago
Position Overview
We are seeking an ML Systems Engineer to optimize the performance and efficiency of large language model inference powering our agentic AI platform. This is a technical role focused on low-level systems optimization. You will implement performance optimizations, build evaluation harnesses, and architect multi-node clusters for training and inference that push the limits of LLM throughput and latency. Your work will directly impact the responsiveness and cost-efficiency of AI agents used by leading semiconductor companies to design chips.
Key Responsibilities
- Design, deploy, and optimize LLM inference systems across multi-node clusters, maximizing throughput and minimizing latency for production workloads.
- Implement and benchmark concrete inference optimizations.
- Profile and analyze inference bottlenecks at the systems level-from GPU kernel execution to memory bandwidth constraints.
- Build robust evaluation harnesses and benchmarking frameworks that measure accuracy, throughput, latency, and resource utilization across various parallelism strategies.
- Collaborate with research scientists to integrate new model architectures and optimizations into production inference infrastructure.
- Investigate and apply emerging techniques from research papers and open-source projects to continuously improve inference performance.
Qualifications
- B.S., M.S., or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
- Experience with large-scale ML systems, GPU computing, or high-performance inference optimization.
- Strong proficiency in Python and C++/CUDA; hands-on experience with SGLang, vLLM, PyTorch, or similar inference frameworks.
- Deep understanding of GPU architecture, memory hierarchies, and parallel computing paradigms.
- Experience deploying and optimizing LLMs in production: model serving, batching strategies, distributed inference, or quantization.
- Strong systems-level debugging and profiling skills; comfort working at multiple layers of the stack from CUDA kernels to application logic.
- Familiarity with distributed computing frameworks (Ray, multi-node training/inference) is a plus.
- Self-directed problem solver who is interested in working on ambitious optimization challenges.
What We Offer
- $150K/yr - $350K/yr + Offers Equity. We are open to discuss above-scale compensation with exceptional candidates on a case-by-case basis.
- Unlimited PTO and full benefits (medical, vision, dental, 401k).
- Two engineering-centric offices with free parking, private gym, and free lunch, drinks and snacks.
Why Join US
- Work on cutting-edge LLM inference optimization problems with real-world production impact.
- Access to substantial GPU compute resources for experimentation and benchmarking.
- Collaborate with a world-class team spanning AI research, systems engineering, and EDA.
- Shape the performance characteristics of AI systems used by leading semiconductor companies.
From ChipAgents's careers page, first listed on Rolev.ai on November 4, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
Rolev.ai is a job search and application tool for US job seekers. For this ML Systems, LLM Post-Training role at ChipAgents, it shows how your resume fits, tailors your resume to the posting, and prepares the application for you to review.
See how you fit
Openings from employer career sites are ranked against your whole resume—and searchable inside Claude, ChatGPT, and Cursor via Rolev.ai MCP.
Tailor without inventing
Every change to your resume is checked against your original. New experience goes in only with your yes—zero fabricated claims.
Draft the full kit
Tailored and Full Match resumes, role-specific cover letters, and answers to employer screening questions are prepared in seconds.
1-Click Extension Autofill
The Chrome extension fills the employer's Greenhouse, Workday, Lever, or Ashby form in 1 click. You review it and press Submit.
Common questions
What is the salary for the ML Systems, LLM Post-Training role at ChipAgents?
The ML Systems, LLM Post-Training posting at ChipAgents states compensation of $150,000 per year. Final pay may depend on location, experience, and interview evaluation on ChipAgents's official career site.
Where is the ML Systems, LLM Post-Training job at ChipAgents located?
This ML Systems, LLM Post-Training position at ChipAgents is located in San Jose, CA. Always check ChipAgents's application page for specific state eligibility or relocation policies.
How do I apply for the ML Systems, LLM Post-Training position at ChipAgents?
This listing links directly to ChipAgents's Ashby application page. You can apply directly on ChipAgents's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.