Staff Machine Learning Engineer

Mural Group; United States; Remote; USD 230,000 - 300,000; Full time

Job summary

Mural Group is seeking a Staff ML Engineer to set the technical direction for its agent systems. This role focuses on multi-step LLM systems, evaluation pipelines and robust deployment for large enterprise customers.

You will design, implement and optimize end-to-end ML workflows, mentor engineers, and help define quality, latency and cost targets in a remote US setting.

Qualifications

• 7+ years shipping ML in production, including LLMs at scale.
• Led the design of complex, multi-step LLM systems.
• Depth in transformers, embeddings and retrieval.
• Evaluation experience beyond single prompts.
• PyTorch or similar on distributed cloud infrastructure.

Responsibilities

• Design multi-step LLM systems: reasoning, retrieval, planning and tool use.
• Own evaluation from offline benchmarks to online experiments and model-graded review.
• Find and fix failure modes such as hallucination and tool misuse.
• Set the quality, latency and cost targets the team builds against.
• Mentor senior engineers and shape how the group works.

Skills

ML production

LLM system design

Transformers & retrieval

Evaluation methods

PyTorch / distributed cloud

Education

BS in CS

Tools

PyTorch

Job description

Location: Remote (US)

Pay: $230,000–$300,000 + bonus + equity

A late-stage, venture-backed enterprise AI company is hiring a Staff ML Engineer to set the technical direction for its agent systems. This is model and systems work that ships to large enterprise customers, not a thin layer over someone else's API.

What you'll do

• Design multi-step LLM systems: reasoning, retrieval, planning and tool use

• Own evaluation, from offline benchmarks to online experiments and model-graded review

• Find and fix failure modes such as hallucination and tool misuse

• Set the quality, latency and cost targets the team builds against

• Mentor senior engineers and shape how the group works

What you bring

• 7+ years shipping ML in production, including LLMs at scale

• Led the design of complex, multi-step LLM systems

• Depth in transformers, embeddings and retrieval

• Evaluation experience beyond single prompts

• PyTorch or similar, on distributed cloud infrastructure

• BS in CS or a related field; MS or PhD a plus

Nice to have: ML shipped before LLMs, then moved into generative AI; detailed retrieval work (chunking, reranking, evals)