Overview
Skills
Job Details
Title: Senior LLM Engineer Contract:12+ Months Location: San Jose, CA (Hybrid)
We are seeking a highly skilled Senior LLM Engineer to design, build, and optimize large language model (LLM) systems from research to production. This role involves developing model architectures, managing distributed training infrastructure, fine-tuning and evaluating model weights, and deploying scalable inference pipelines. The ideal candidate has deep expertise in transformer-based architectures, GPU/TPU optimization, and prompt or instruction tuning. You'll collaborate with cross-functional teams to advance our LLM capabilities, improve efficiency, and deliver high-performance generative AI solutions.
Key Responsibilities:
- Design, train, and fine-tune large language models using PyTorch or JAX.
- Manage distributed training and model optimization across GPTPUs.
- Develop and maintain scalable LLM infrastructure for experimentation and deployment.
- Evaluate model performance and implement techniques for continual learning and alignment.
- Collaborate with ML researchers and product teams to integrate LLMs into real-world applications.
Qualifications:
- 5+ years in ML/AI engineering, with 2+ years focused on large-scale language models.
- Strong understanding of deep learning frameworks (PyTorch, TensorFlow, JAX).
- Experience with model parallelism, quantization, and fine-tuning techniques.
- Familiarity with MLOps tools, vector databases, and cloud infrastructure (AWS, Google Cloud Platform, Azure).
- Background in NLP, transformer architectures, and reinforcement learning from human feedback (RLHF) a plus.
EEO, ADA, FMLA Compliant
VLink is an equal opportunity employer. At VLink, we are committed to embracing diversity, multiculturalism, and inclusion. VLink does not discriminate on the basis of race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. All aspects of employment including the decision to hire, promote, or discharge, will be decided on the basis of qualifications, merit, performance, and business needs.