You're an engineer who dreams in cycles and optimizations. You have a deep passion for squeezing every ounce of performance out of complex systems, whether that's rendering the latest AAA game title or optimizing large-scale distributed systems.
At Replicate, we're building the fastest way to deploy machine learning models. We're looking for someone who can bring their performance optimization expertise to the cutting edge of AI infrastructure.
We're looking for the right person, not just someone who checks boxes, so you don't need to satisfy all of these things. But, you might have some of these qualities :
- Mastery of C++ and a deep understanding of systems programming. You know your way around pointers, memory management, and low-level optimizations.
- Experience with high-performance computing environments. Whether it's game engines, financial systems, or scientific simulations, you've worked on projects where every microsecond counts.
- Comfort with parallel programming models. You've wrestled with multi-threading, SIMD instructions, or GPU programming (like CUDA or similar).
- A track record of optimizing large-scale production deployments. You understand the challenges of performance at scale and how to address them.
- An insatiable curiosity about new technologies and techniques. You're always looking for the next tool or approach that could give your code that extra boost.
- Excellent problem-solving skills. You enjoy diving into complex performance issues and emerging with elegant, efficient solutions.
You might be particularly good for this job if :
- You've optimized rendering pipelines for video games or real-time graphics applications.
- You've worked on high-frequency trading systems where nanoseconds make a difference.
- You've contributed to open-source projects focused on performance-critical libraries or tools.
- You get excited about diving into unfamiliar codebases and finding unexpected optimizations.
- You have experience profiling and optimizing applications across different hardware architectures.
While prior experience with AI or machine learning isn't required, you should be excited about applying your performance optimization skills to this domain.
We believe your expertise in cycles, memory management, and systems-level thinking will translate well to the challenges of optimizing AI model inference and training.
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