Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Designing, building, and maintaining production-grade ML infrastructure for image and 3D generative models with an accent on backend services, API design, and model optimization. Focus on deploying and operating ML models at scale, solving concurrency challenges, and improving end-to-end system efficiency.

Location: Hybrid, based in Los Angeles or San Francisco, United States

Salary: $215,000–$275,000

Company

hirify.global is an avatar technology company powering the next era of interactive digital identity through AI companions.

What you will do

• Design, build, and maintain production-grade ML infrastructure.
• Develop backend services and APIs that support model inference at scale.
• Deploy, monitor, and operate ML models on cloud and large-scale platforms.
• Optimize inference pipelines using model acceleration techniques (quantization, pruning, mixed precision, ONNX/TensorRT).
• Partner with ML researchers to productionize diffusion models, transformer-based models, and 3D generation systems.
• Improve end-to-end system efficiency across data loading, inference, post-processing, and storage, while supporting rapid experimentation.

Requirements

• Strong experience building backend and infrastructure systems in production environments.
• Proficiency in Python and experience designing APIs/services (FastAPI, Flask, gRPC).
• Hands-on experience deploying and operating GPU-based ML models at scale.
• Experience with cloud platforms (AWS, GCP) and ML deployment stacks (Docker, containers, CI/CD).
• Solid understanding of systems performance, debugging, and reliability engineering.
• Experience supporting real user traffic, not just offline research workflows.

Nice to have

• Experience with generative models (diffusion, transformer-based, multimodal image/3D pipelines).
• Familiarity with 3D generation or computer graphics pipelines.
• Hands-on experience with model optimization and acceleration (quantization, pruning, distillation, ONNX Runtime, TensorRT).
• Experience with distributed systems or scalable inference frameworks (Ray, Triton, TorchServe).
• Background in machine learning fundamentals (training, evaluation, model behavior).

Culture & Benefits

• Work with a team that offers learning and professional development opportunities.
• Shape your career with innovative contributions to a nascent team and product.
• Enjoy the culture and perks of a startup, with the stability of being well funded.
• Comprehensive health, dental, and vision insurance for you and your family.
• Flexible paid time off, sick time, and paid company holidays, plus parental leave.
• Health & wellness support through programs like monthly wellness reimbursement.