Join a talented team at Ghost to tackle unsolved problems in agentic systems and product development.
Posted by employer 2 days ago
First seen on Joblaze 2 days ago
Last verified on the company career page 8 hours ago
Skills & Technologies
Must have
- Use agents to write >90% of your code
- Have done exceptional things in the past
- Have the endurance to prompt 12hrs+ in a day
AI in the day-to-day
Use agents to write >90% of your code.
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
The Member of Technical Staff in Inference at Ghost focuses on developing advanced personal agents, engaging in hands-on coding and problem-solving on a daily basis. Proficiency in using agents for coding and a strong background in AI are essential for this role. It is best suited for highly skilled individuals with a track record of exceptional achievements and the stamina to work intensively. Ghost's team comprises talented professionals from top quant firms and universities, all dedicated to creating impactful products.
Joblaze insights
- Listed 2 days ago — first seen on Joblaze October 15, 2026. Last confirmed on Ghost's careers page October 17, 2026.
- AI/ML appears in 33.8% of 281 comparable staff ai/ml roles in United States.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML.
- What seniority level is this role?
- Ghost targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff - Inference role at Ghost.
From the original posting
About Ghost
Ghost is a personal AI hardware company.
To realize the full benefit of what models will do for people, we believe an entirely new platform will be built around AI. Some devices will let your AI understand what is happening around you, others will enable you to get things done without navigating apps or menus.
As these systems become more capable and more personal, it matters who owns them. We’re building a future where that intelligence belongs to you, with an ecosystem of devices and software that gives you greater control over your time, attention, and the things you want to accomplish.
What you'll do
Build and optimize the inference stack that runs personal AI models locally on Core.
Improve latency, throughput, and memory efficiency across interactive requests and background agent workloads.
Profile performance across the hardware and software stack, optimizing kernels, memory movement, and runtime execution.
Build benchmarks that reflect real product workloads, including long contexts, concurrent agents, and sustained operation.
Work closely with the hardware, post-training, and product teams.
Who you are
Experience building or optimizing inference systems for language models.
Strong systems programming skills in C++ or similar languages, alongside proficiency in Python.
Familiarity with GPU architecture, memory management, and performance profiling.
Experience with inference runtimes, quantization, or GPU kernel development using CUDA, Triton, or equivalent tools.
Strong experimental judgment: you can identify bottlenecks and evaluate tradeoffs between speed, memory, power, and model quality.
Ability to work on-site in San Francisco.
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