Senior LLM Engineer

Posted Aug 20

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Refine foundation models utilizing LoRA/QLoRA, RLHF/DPO, and instruction tuning tailored for domain-specific applications and terminology.

• Develop agentic and tool-use workflows that link LLMs with internal engineering tools and data sources.

• Create evaluation frameworks focused on factuality and precision.

• Take ownership of hallucination and safety measures.

• Construct RAG pipelines using Azure AI Search.

• Develop structured tool-use and function-calling systems on fine-tuned Azure OpenAI models.

• Implement and enhance inference through quantization, KV-cache, vLLM, and TensorRT-LLM on Azure Kubernetes Service.

• Collaborate with ML engineers, data scientists, and MLOps teams to ensure Azure AI/ML training and inference workloads remain reliable, secure, and cost-effective.


⛳️ Requirements

• A minimum of 8 years of comprehensive ML/AI engineering experience, with extensive hands-on work with LLM/foundation models.

• Proven expertise in fine-tuning models using LoRA/QLoRA/PEFT, complete fine-tuning, or pretraining at scale.

• Practical knowledge of RLHF, RLAIF, DPO, or instruction tuning.

• Strong proficiency in Python programming.

• Advanced skills in PyTorch.

• A solid understanding of the internals of transformer architecture.

• Practical experience in building RAG pipelines, embeddings/vector search, and agentic or tool-use LLM systems.

• Familiarity with Azure OpenAI, Azure AI Foundry, or a similar cloud LLM platform.

• Direct experience with Azure OpenAI Service and Azure AI Foundry is preferred.

• Experience in orchestrating LLM-driven code or structured-output generation for technical or engineering fields is preferred.

• Distributed training experience across multi-GPU/multi-node clusters, using DeepSpeed or FSDP, is preferred.

• Publications, blog posts, or contributions to open-source projects in generative AI are preferred.


🏝️ Benefits

• Variable pay, offered as a monetary bonus or in an alternative format.

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Flexible spending accounts.

• Health savings accounts.

• Life insurance.

• Accidental Death & Dismemberment (AD&D) insurance.

• Disability insurance.

• Retirement benefits.

• Paid vacation/time off.

• Educational assistance.

• Infertility assistance.

• Paid parental leave.

• Adoption assistance.

• Flexible work environment.

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