Senior LLM Engineer

About the Role

The Senior LLM Engineer will fine-tune and deploy LLMs on Azure OpenAI / Azure AI Foundry to power generative AI capabilities within our engineering design platform, translating natural-language design intent into structured, engineering-valid outputs.

About Our Team

Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, working alongside ML engineers, data scientists, and MLOps teams to keep training and inference workloads reliable, secure, and cost-efficient.

Responsibilities

• Fine-tune foundation models (LoRA/QLoRA, RLHF/DPO, instruction tuning) for domain-specific tasks and terminology.
• Build agentic and tool-use workflows that connect the LLM to internal engineering tools and data sources.
• Design evaluation harnesses for factuality and accuracy; own hallucination and safety guardrails.
• Build RAG pipelines (Azure AI Search) and structured tool-use/function-calling systems on top of fine-tuned Azure OpenAI models.
• Deploy and optimize inference (quantization, KV-cache, vLLM/TensorRT-LLM) on Azure Kubernetes Service for cost-efficient serving.

Requirements

• 8+ years overall ML/AI engineering experience, with deep hands-on LLM/foundation model work — not just calling APIs.
• Demonstrated experience fine-tuning models (LoRA/QLoRA/PEFT, full fine-tuning, or pretraining at some scale).
• Practical experience with alignment techniques (RLHF, RLAIF, DPO, or instruction tuning).
• Strong Python and deep PyTorch proficiency; solid grasp of transformer architecture internals.
• Hands-on experience building RAG pipelines, embeddings/vector search, and agentic or tool-use LLM systems.
• Familiarity with Azure OpenAI / Azure AI Foundry or an equivalent cloud LLM platform.

Preferred Qualifications

• Direct experience with Azure OpenAI Service and Azure AI Foundry for enterprise-scale deployment.
• Experience orchestrating LLM-driven code or structured-output generation for technical/engineering domains.
• Distributed training experience across multi-GPU/multi-node clusters (DeepSpeed, FSDP).
• Publications, blog posts, or open-source contributions in generative AI.

Pay

For this role, we anticipate paying $195,000 - $255,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

Benefits

Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength, focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes:

• Medical, dental, and vision insurance
• Flexible spending and health savings accounts
• Life insurance, ADD, and disability
• Retirement plans
• Paid vacation/time off
• Educational assistance
• Infertility assistance, paid parental leave, and adoption assistance (eligibility criteria apply)

Specific eligibility criteria is set by the applicable Summary Plan Description, policy, or guideline, and benefits may vary by geographic region.