Own the inference systems that power frontier AI models in production and research at a tech-first startup.
Posted by employer 2 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
We are building a frontier AI research company and training our own models end-to-end.
Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In this role, the engineer is responsible for developing and optimizing inference systems that support both research and production for advanced AI models. Key skills include expertise in high-throughput serving systems, GPU optimization, and distributed inference frameworks. This position is ideal for experienced engineers with a strong background in AI and systems architecture, particularly those eager to tackle complex performance challenges. Mirendil is focused on pioneering AI research, making this an exciting opportunity to contribute to cutting-edge technology.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Mirendil's career page.
- Mirendil has 13 other open roles including Executive Assistant & Operations , Member of Technical Staff, Kernels, Member of Technical Staff, Recursive Self-Improvement (RSI).
- 5149 active AI/ML roles on Joblaze right now.
- 127 active GPU roles on Joblaze right now.
- 52 active vLLM roles on Joblaze right now.
- Salary band is above the typical range for AI/ML roles (median ~$188,000).
- Pays more than 89% of the 2239 salaried AI/ML roles we track (median $180,000). See AI/ML salary trends
Quick facts
- What's the salary range?
- Mirendil lists $300,000–$400,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, GPU, SGLang, TensorRT-LLM, vLLM.
- What seniority level is this role?
- Mirendil targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff, Inference role at Mirendil.
From the original posting
Mirendil
Mirendil is a tech-first company focused on solving core bottlenecks that unlock step-change acceleration across science and technology. Our first goal is to democratize frontier AI R&D across scientific disciplines. We are building a frontier AI research company and training our own models end-to-end.
The Role
We are looking for an engineer to own the inference systems that power our models in production and research. You'll work across the full inference stack, from serving infrastructure down to hardware-level optimization. Some example areas you might work on (not limited to):
Design and build high-throughput, low-latency inference serving systems for frontier models, optimizing for both research iteration and production deployment
Optimize inference performance across GPU and accelerator hardware - maximizing FLOPs utilization, memory bandwidth, and compute efficiency for large-scale models
Enable and extend distributed inference frameworks (e.g. vLLM, SGLang, TensorRT-LLM) to support novel architectures, long-context workloads, and agentic inference patterns
Implement and validate inference-time optimizations: speculative decoding, quantization, KV cache management, and batching strategies
Build observability and reliability infrastructure so the team can measure latency, throughput, and cost across every serving configuration
Partner directly with teams to bring new model architectures and post-training techniques into production quickly
If you're excited about pushing the performance limits of frontier model inference, we'd love to hear from you.
We offer a base salary of $300,000–$400,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.