LLM Engineer

Job Title: LLM Engineer Job Type: Contract (W2 Only) Contract Duration: ASAP through 12/31/2025 (with good potential for extension into 2026) Work Location: San Jose, CA (HYBRID role; Onsite 2 days per week) Work Schedule/Hours: Monday–Friday, 8 hours per day, 40 hours per week (standard business hours) Compensation: $85 to $95 per hour Overview: A leading Big Four consulting firm is seeking a highly-skilled LLM Engineer to design, train, and optimize large language models that drive cutting-edge applications in generative AI and natural language understanding. This role offers the opportunity to work on advanced model development, scalable deployment systems, and innovative research alongside cross-functional product and engineering teams. Responsibilities: Model Development & Optimization • Design, train, fine-tune, and evaluate large language models (LLMs) to ensure high performance, efficiency, and alignment with research or product goals. • Optimize model architectures, tokenization strategies, and data pipelines to enhance throughput and model accuracy. Systems Integration & Deployment • Build and maintain scalable inference pipelines for production environments. • Optimize serving infrastructure using techniques such as quantization, caching, pruning, and distillation. • Integrate trained models into enterprise applications, APIs, or end-user products. Research & Cross-Functional Collaboration • Lead experimentation with new architectures, retrieval-augmented generation (RAG) frameworks, and prompt-engineering techniques. • Collaborate closely with product managers, data scientists, and ML operations teams to translate research into production-grade solutions. • Stay current with advancements in transformer architectures, fine-tuning methods, and LLM safety/alignment best practices. Qualifications: Required: • High school diploma or GED required; Bachelor’s degree or higher preferred. • 5+ years of experience in machine learning, NLP, or large-scale model development. • Strong understanding of deep learning frameworks such as PyTorch or TensorFlow. • Experience building, training, or fine-tuning large language models (e.g., GPT, LLaMA, PaLM, Falcon, etc.). • Solid programming skills in Python, with experience in distributed training and cloud-based ML infrastructure (AWS, GCP, or Azure). • Strong problem-solving and communication skills, with the ability to work cross-functionally in fast-paced environments. Preferred: • Experience with retrieval systems, vector databases, or RAG pipelines. • Familiarity with model alignment, evaluation metrics, and responsible AI practices.