About the job
About GenPeach AI
GenPeach AI stands at the forefront of innovation, transforming how individuals create and engage with AI-driven technology. Our product-focused research lab is dedicated to developing advanced multimodal AI that resonates emotionally with users.
We specialize in constructing vertical foundation models that generate hyper-realistic representations of humans in both image and video formats. Our technological framework includes utilizing vast proprietary datasets, formulating cutting-edge model architectures, and training these models effectively on substantial GPU clusters, all while seamlessly integrating them into user-facing products.
With our focus on training and deploying large-scale models, we bridge the gap between research-grade AI and production-quality systems engineering, ensuring our solutions are not just theoretical but are actively contributing to real-world applications.
About the Role
We are searching for a Member of Technical Staff (MTS) who will take ownership of and enhance the AI infrastructure that supports both our research and production systems.
This pivotal infrastructure role offers significant ownership and a direct impact on model training, inference performance, and developer productivity.
In this role, you will
Lead the AI execution and infrastructure layer utilized by our research and product teams.
Design and develop high-performance Python systems for:
Scalable model inference
Training orchestration
Large-scale data processing
Collaborate closely with research and backend engineers to implement models and expose them through APIs.
Design and manage distributed pipelines and task queues for both batch and streaming workloads.
Enhance GPU inference for latency, throughput, and cost efficiency.
Oversee the MLOps lifecycle, including model deployment, versioning, monitoring, and alerting.
Build and sustain CI/CD pipelines for services and ML workflows.
Identify and resolve performance bottlenecks across Python, GPUs, networking, and storage.
Contribute to the architectural design and long-term infrastructure decisions.
Minimum Qualifications
5+ years of professional experience in software engineering with a focus on Python.
Extensive knowledge of Python, including asynchronous programming, multiprocessing, concurrency, performance profiling, and optimization techniques.

