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About the Role
Mount Thor is building a production inference platform on Apple Silicon, offering elastic compute through developer-friendly interfaces. You will own the stack from GPU kernels and model execution to distributed scheduling, networking, and customer-facing serving systems, establishing the technical foundation for inference at the company.
Responsibilities
- Build and optimize the inference engine, implementing model execution, scheduling, KV-cache management, and optimizations like quantization and speculative decoding.
- Write performance-critical kernels and runtime code, optimizing operations across Metal, MLX, and compiler internals.
- Design for Apple Silicon, considering unified memory, bandwidth, compute capabilities, and OS behavior.
- Build distributed inference and its communication layer, implementing model sharding and optimizing collective communication.
- Own inference scheduling and routing, building request queues, admission control, and autoscaling.
- Ship a production inference service, building model loading, serving APIs, and integrating with fleet systems.
- Make performance reproducible by building benchmarks and profiling tools.
- Set the engineering direction, turning customer workloads into technical priorities and contributing to open-source projects.
Requirements
- A record of building and optimizing production inference engines, GPU compute software, or distributed ML systems, with substantial depth in at least one and hands-on work across multiple layers.
- Strong systems programming skills in C++ or Rust, proficiency in Python, and experience working inside performance-critical libraries and runtimes.
- A practical understanding of transformer inference, including attention, prefill and decode, batching, KV caches, quantization, and their compute and memory costs.
- Experience with GPU programming and performance analysis, including memory hierarchies, parallel execution, synchronization, and numerical precision.
- Strong distributed-systems fundamentals, including scheduling, concurrency, networking, failure handling, and resource management.
- Experience taking software from architecture through production deployment, debugging, and ongoing operation.
- The ability to turn an ambiguous performance problem into a measured bottleneck, an implementation, and a verified improvement.
- The judgment and ownership to establish a new technical area, prioritize the work, and explain tradeoffs clearly to engineers and customers.
Skills
- C++
- Rust
- Python
- GPU programming
- Performance analysis
- Distributed systems
- Transformer inference
- Metal
- MLX
Location
- Remote
Work Type
- Full-time
Experience Level
- Founding
About the Company
- Mount Thor makes Apple hardware—macOS and Apple Silicon—available at datacenter scale for AI workloads.
- We build the infrastructure around that hardware to deliver elastic compute through developer-friendly interfaces.
- We are building an inference platform that gives developers a straightforward way to deploy and serve models on Apple Silicon, backed by deep engineering across hardware, runtimes, and distributed systems.