ML Solution Architect (Early Talent)

Responsibilities: Develop, test, and optimize LLM-powered applications and multimodal AI solutions. Collaborate with senior architects to perform benchmarking, inference optimization, and create scalable deployment workflows.

Requirements: Requires a degree in Computer Science, AI, or a related field with strong Python programming skills. Candidates should have hands-on experience with machine learning frameworks like PyTorch and generative AI technologies.

Key skills: Python, PyTorch, Transformers, Generative AI, LLM Deployment, Prompt Engineering, Inference Optimization, Machine Learning, Cloud Platforms, MLOps, Docker, Kubernetes, Git, vLLM, SGLang, TensorRT-LLM

Keywords: Machine Learning, Generative AI, LLM, Python, PyTorch, Transformers, vLLM, SGLang, TensorRT-LLM, Quantization, Batching, Caching, Routing, MLOps, Docker, Kubernetes, Git, Cloud Computing, Inference Optimization, Multimodal Models, Prompt Engineering, Benchmarking, AI Infrastructure, Solution Architecture