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Build and deploy AI/ML models in Python for HR software, integrating them with backend systems using Django and Kubernetes.
Principal consultant advising enterprises on Generative AI, Agentic AI, and ML transformations on AWS, leading large-scale implementations and shaping cloud strategies for industries like FSI, telecom, and retail.
Integrates AI/ML components into manufacturing applications using Azure cloud services, SQL databases, and microservices architecture.
Build AI/ML-powered features for ClickHouse Cloud, integrating inference APIs and user interfaces to help users extract value from data using TypeScript and React.
Build and deploy NLP models and GenAI features for a legal AI platform, maintaining production systems and collaborating with cross-functional teams.
Build and optimize large-scale AI/ML systems for Google Cloud, leveraging distributed computing and advanced algorithms to power services like Search and YouTube.
Build and maintain ML benchmarks and evaluation tools to assess model performance and guide improvements.
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 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.
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