Senior LLM Engineer

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.

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

• Medical, dental, vision, flexible spending and health savings accounts.
• Life insurance, ADD, disability, retirement.
• Paid vacation/time off, educational assistance.
• May include infertility assistance, paid parental leave, and adoption assistance.