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Build and evaluate MLOps pipelines for cutting-edge GenAI models using JAX, PyTorch, and GPU kernels (Pallas/Triton) to improve training data quality.
Staff Applied Scientist at Apple builds and optimizes compact LLMs for Siri’s UI control, tool calling, and conversational features, focusing on mobile hardware constraints and post-training techniques.
Design and partition cutting-edge AI models (e.g., Transformers) for custom silicon, mapping them to heterogeneous ASICs before hardware tape-out and ensuring cycle-accurate performance.
Design and deploy secure, scalable cloud infrastructure on GCP for enterprise customers, guiding migrations and modernizations while optimizing for performance and cost.
Build and optimize low-latency ML inference pipelines and LLM tools to automate trading workflows, using PyTorch, TensorRT, and cloud GPUs.
Build and optimize a compiler stack for robotics simulation and AI training, using LLVM, JIT, and GPU codegen to maximize performance.
Build and maintain insurance-focused microservices and APIs using Java, Docker, and AWS, while collaborating in an Agile team that values TDD and GraphQL.
Build AI-driven simulation models to predict physical-system behavior for engineering and manufacturing, using deep learning and probabilistic methods in Python.
Build and optimize CUDA Core Libraries (C++/Python) like Thrust and CUDA-Python that power GPU-accelerated software for AI, HPC, and data analytics.
Build and deploy large language models to automate real-world processes in healthcare, government, and energy sectors, turning research into production-grade AI solutions.
Build and deploy production-grade AI models (LLMs, agents, RAG) to automate workflows in healthcare, government, and energy sectors.
Build and own core ML systems for an AI-native assistant that handles long-running tasks, retains context, and interacts with tools to automate everyday workflows using Python, PyTorch/JAX, and GPU-based training/inference.
Build and improve core ML components for an AI-native assistant that handles long-running tasks, retains context, and interacts with external tools in production systems.
Build and ship AI features end-to-end, designing prompts, workflows, and systems to turn raw model outputs into reliable product behavior in production.
Builds and maintains Java-based components for a fund-transfer and investor-onboarding platform using Spring Boot, JPA, and REST/SOAP services.
Build and deploy deep-learning models for 3D vision and robot perception, turning transformer-based research into production-ready grasping and manipulation systems for industrial robots.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Lead the design and deployment of AI/ML features for a commercial real estate SaaS platform, including LLM-powered tools and custom domain models, while setting engineering standards and mentoring teams.
Build and operate the ML infrastructure powering an AI assistant, focusing on model training, deployment, inference, and observability to enable reliable, scalable, and cost-efficient production systems.
Build and ship LLM-powered AI agent workflows that orchestrate multi-step tasks, integrate tools, and turn probabilistic model outputs into reliable user experiences.
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