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Build and deploy scalable AI/ML systems using Python, Azure, Databricks, and MLOps/LLMOps tooling to solve business problems at a sustainability-focused company.
Build and deploy ML models to detect abuse and protect Apple’s ecosystem, using LLMs and deep learning while ensuring user privacy and security.
Develop and optimize LLVM/MLIR-based compilers for Mobileye’s EyeQ hardware, focusing on low-level code analysis and performance tuning for autonomous-driving systems.
Build and maintain Go-based data pipelines, real-time analytics, and ML models for a large-scale messaging platform using Kafka, ClickHouse, and Kubernetes.
Build and deploy cutting-edge text-to-speech models, voice cloning, and audio generation systems using large-scale ML and transformer architectures.
Lead AI/ML engineer building and scaling secure, cloud-based data platforms at JPMorganChase, mentoring teams and driving AI-assisted development practices.
Build and ship GenAI image/video generation and editing models (diffusion, flow-matching) that power Snapchat’s AI Lenses for millions of users daily.
Principal ML Engineer at Faculty designs and steers large-scale AI systems for defence clients, setting technical direction and mentoring teams while ensuring scalable, ethical deployments.
Design and lead ML architecture for sports-tech products, building scalable inference pipelines and real-time 3D systems that power immersive fan experiences.
Build and deploy ML models for real-world operational challenges using Python and modern frameworks, focusing on time-series, forecasting, and optimisation.
Lead the build and deployment of production-grade AI systems, fine-tuning large language models and optimizing GPU-based training/inference pipelines.
Build and deploy production-scale NLP and personalization models that process billions of consumer reviews and UGC, using Python, cloud ML stacks, and LLMs.
Design and build AI agents and ML models for a government-focused AI platform, integrating RAG pipelines and enterprise data to power secure, compliant automation.
Build and scale ML-powered recommendation and personalization systems for a cannabis retail platform, designing ranking, retrieval, and forecasting models to improve eCommerce experiences.
Build, validate, and maintain Python-based machine learning models to turn raw data into business insights and drive decisions.
Build, fine-tune, and benchmark ML models, including quantum-inspired and LLM solutions, while optimizing performance and prototyping new approaches.
Build and optimize large-scale generative language models (LLMs) for GigaChat, focusing on Russian-language performance, distributed training, and efficiency improvements.
Build and optimize multi-agent LLM systems and RAG pipelines for city-scale digital services using Python, FastAPI, and async pipelines.
Lead AI/ML initiatives at J.P. Morgan, applying advanced machine learning to problems like NLP, speech analytics, and reinforcement learning.
Lead the design and productionization of ML systems at scale for a large fintech company, focusing on architecture, code review, and high-availability deployments.
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