Senior Machine Learning Engineer

What you'll do

• Design, build, and operate backend cloud services for ML and Generative AI features across multiple products.
• Architect and optimize GPU-accelerated inference pipelines for scalability, cost efficiency, and reliability.
• Optimize models using quantization, pruning, graph optimization, and hardware-aware tuning to improve performance.
• Analyze and improve the performance, quality, stability, and throughput of end-to-end AI workflows.
• Lead the integration of new ML models into production through validation, regression testing, and evaluation.
• Build and maintain CI/CD pipelines for a suite of ML-backed microservices.
• Ensure services meet production standards for observability, monitoring, logging, and incident response.
• Participate in on-call rotations and provide production support to ensure operational excellence.

What we're looking for

• Over 5 years of experience building, optimizing, and operating ML systems in production with GPU-based workloads.
• Proven experience designing large-scale, reliable cloud services with high performance and availability requirements.
• Strong background in model serving and inference optimization, including conversion, compression, and orchestration.
• Hands-on experience with computer vision and/or generative models such as GANs, diffusion models, CLIP, or MLLMs.
• Proficiency in Python, PyTorch, TensorFlow, NVIDIA Triton, TorchServe, ONNX, AIT, AOT, and CUDA.
• Proficiency with infrastructure tools including Docker, Kubernetes, and AWS.
• Solid understanding of GPU systems, drivers, and deployment considerations in cloud environments.
• Ability to work independently on complex systems while collaborating effectively across teams.