Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure.
Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues.
Apply and scale optimization techniques across a wide range of ML models, particularly large language models.
Collaborate with a diverse team to design and implement innovative solutions.
Own projects from idea to production.

Requirements

Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field.
Experience with one or more general-purpose programming languages, such as Python or C++.
Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching).
Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM.
Demonstrated interest and experience in LLM’s.
Deep understanding of GPU architecture.
Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs) (Bonus).
Experience with CUDA or similar technologies (Bonus).
Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions (Bonus).
Experience with Docker and Kubernetes (Bonus).

Benefits

Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents
Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonC++quantizationspeculative decodingML model inferenceLLM optimization techniquesPyTorchTensorRTCUDAsoftware engineering principles

Soft Skills

collaborationproject ownershipproblem-solving