Machine Learning Engineer, Genies

• Strong experience building backend and infrastructure systems in production environments
• Proficiency in Python and experience designing APIs/services (e.g., FastAPI, Flask, gRPC)
• Hands-on experience deploying and operating ML models at scale, including:
• GPU-based inference services
• Concurrency handling and request batching
• Latency and throughput optimization
• Experience with cloud platforms and ML deployment stacks, such as:
• AWS (SageMaker, EC2, EKS), GCP, or similar
• Docker, containers, CI/CD pipelines
• Solid understanding of systems performance, debugging, and reliability engineering
• Experience supporting real user traffic, not just offline research workflows

Desirable

• Genies is looking for a ML Infra and Model Optimization Engineer to join our R&D team. Based either in our Los Angeles or San Francisco offices (Hybrid), you will work closely with a dedicated and talented team of technical artists, engineers and artists
• Together, you will explore new concepts and technologies to further Genies' mission of empowering users to develop their own avatar ecosystems. We're looking for someone who is passionate about creating high-quality visuals and has the technical foundation to help us build the next wave of digital identity
• Design, build, and maintain production-grade ML infrastructure for image and 3D generative models
• Develop and own backend services and APIs that support model inference at scale (high concurrency, low latency, high reliability)
• Deploy, monitor, and operate ML models on cloud and large-scale platforms (e.g., SageMaker, Kubernetes, Ray Serve, custom GPU services)
• Optimize inference pipelines using model acceleration techniques such as:
• Quantization, pruning, mixed precision
• ONNX / TensorRT / torch.compile
• Partner with ML researchers to productionize diffusion models, transformer-based models, and 3D generation systems
• Implement evaluation, logging, monitoring, and alerting to ensure system stability and performance
• Improve end-to-end system efficiency across data loading, inference, post-processing, and storage
• Support rapid experimentation while maintaining production safety and scalability
• You'll work with a team that you’ll be able to learn from and grow with, including support for your own professional development
• You'll be at the helm of your own career, shaping it with your own innovative contributions to a nascent team and product
• You'll enjoy the culture and perks of a startup, with the stability of being well funded