ML Systems Engineer — Inference Stack

Job description

Groq is hiring a ML Systems Engineer — Inference Stack (Full-time) remote (US). This llm engineer role is part of the AI hiring market in Remote (US) (United States). Remote US Groq ML systems role — runtime, scheduling, and developer APIs for high-throughput LLM inference. Listed compensation: $160k – $220k / year. Stack: ML systems, Remote, Groq, C++, LLM.

LLM Engineer profiles are in high demand in Remote (US): Fully remote US roles: LLM Engineer, MLOps, Data Scientist, and AI Product Manager. Apply from any state.…

The team

Groq — AI team

Responsibilities

• Ship production AI features with clear quality, latency, and safety bars
• Partner with product, design, and infra on roadmap priorities
• Document evals, monitoring, and responsible AI practices

Requirements

• 3+ years shipping ML, LLM, or data systems in production (or strong internship + portfolio)
• Strong Python or TypeScript and clear written communication
• Comfort with evals, observability, and cross-functional US teams

Tech stack

Benefits

Hiring process

1. 1Recruiter screen
2. 2Technical interview
3. 3Team conversation
4. 4Offer

Experience: Mid · 3+ years · Education: BS/MS CS, ML, or equivalent experience

FAQ — ML Systems Engineer — Inference Stack

What is the salary for ML Systems Engineer — Inference Stack at Groq?

Listed range: $160k – $220k / year (Full-time). Packages often include PTO, remote options, and equity depending on the company.

Where is the ML Systems Engineer — Inference Stack role based?

US remote role. The team may be headquartered in Remote · US.

How do I apply to Groq?

Create a free Ganloss candidate account, then apply in one click. Job reference: EXP-2026-0020. Process: Recruiter screen → Technical interview → Team conversation → Offer.

Is Groq hiring other AI roles?

Groq (AI hardware & inference) hires across LLM, ML, data, and AI product. See all openings on the Ganloss company page.

Your profile is sent directly to Groq's hiring team.