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Leads AI/ML engineering at BlackRock, designing and deploying generative AI, intelligent agents, and predictive systems to transform asset management and financial services. Sets technical direction, builds scalable AI platforms, and partners across business teams to deliver production-grade solutions.
Designs and deploys AI/ML solutions (LLMs, RAG, predictive models) to optimize sales performance, forecasting, and operational efficiency using CRM/data analytics.
The AI Engineer will design, develop, and deploy AI-powered solutions, including machine learning models, intelligent agents, and copilots, using Python and Azure cloud platforms. This role involves collaborating with cross-functional teams to integrate AI into enterprise applications while adhering to responsible AI and security standards.
Build and deploy enterprise-grade AI systems, from prototypes to production, integrating LLMs and agentic workflows while ensuring reliability, security, and cost efficiency.
The Data Scientist will develop and deploy advanced NLP and machine learning models to support national security initiatives. The role involves using Python, PyTorch, TensorFlow, and Hugging Face to perform text analytics and statistical modeling on large datasets.
Build and operate production ML models and AI-driven systems for anomaly detection across Disney's streaming platforms (Disney+, Hulu, ESPN). Core tech: Python, PyTorch, FastAPI, MLflow, AWS/EKS, Docker, and time-series data processing.
Tech Lead / Senior Software Engineer designing and deploying AI-driven solutions using Python, Azure AI services, and ML frameworks like TensorFlow or PyTorch, with DevOps and video analytics integration.
ML Engineer on ByteDance's e-commerce recommendation and marketing algorithm team, building user growth engines, personalized push/email recommendations, and uplift models using C++, Python, big data tools, and deep learning frameworks.
Develop and deploy machine learning models for fraud detection and risk prevention in ByteDance's e-commerce ecosystem, building data pipelines and analyzing security data to identify abnormal behavior patterns.
Solution Architect designing AI/ML solutions for enterprise clients, with hands-on engineering in Python, cloud infrastructure (Kubernetes, Docker, Terraform), and modern AI ecosystems (LangChain, Hugging Face, vector databases).
Build end-to-end product features connecting Next.js frontends with Python/Node.js backends and LLM-powered AI inference pipelines, designing autonomous agent workflows with a focus on reliability and real-time interaction.
Build and deploy production-grade AI models for geospatial applications, leading ML system design, MLOps, and cross-team collaboration.
Senior AI & Full-Stack Engineer leading development and production deployment of AI/ML capabilities (LLMs, RAG, credit/fraud models) and full-stack features on a Singapore SME financing marketplace, using Python, SQL, and cloud platforms.
Forward-deployed data scientist at SAP designing and deploying advanced ML and statistical solutions directly in customer environments, using Python, SQL, and frameworks like TensorFlow/PyTorch on top of SAP data platforms.
Lead end-to-end development of AI solutions—prototyping, fine-tuning vision/language/multimodal foundation models, and deploying agentic AI systems for enterprise clients—using Python and PyTorch.
Leads AI/ML system design, development, and deployment for geospatial applications, focusing on scalable production models, MLOps, and cross-team collaboration to integrate AI into platforms.
Lead the design and deployment of production-grade AI/ML solutions focused on geospatial applications, applying MLOps best practices and mentoring engineers using Python, PyTorch, scikit-learn, OpenCV, Docker, and API frameworks.
Builds and optimizes an internal AI CodeGen platform to automate code generation, testing, and developer workflows using LLMs, RAG, and cloud infrastructure.
Designs and deploys AI/ML solutions (including generative AI) to optimize sales performance, forecasting, and operational efficiency using CRM/data analytics, with a focus on enterprise-scale MLOps and sales ops integration.
Designs, builds, and deploys AI/ML systems on Google Cloud to solve business problems, focusing on model optimization, MLOps pipelines, and agentic AI workflows for Crate & Barrel’s core products.
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