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Build and optimize low-latency, high-throughput ML inference services for CTR/CVR prediction and generative recommendation using LLMs, focusing on GPU acceleration and end-to-end pipeline optimization.
Build and optimize high-performance ML kernels and compilation systems for recommendation/inference platforms powering apps like TikTok and Douyin.
Build backend services for autonomous logistics vehicles, including fleet tracking, route optimization, and IoT data pipelines using Python/Java/Golang and cloud-native tools.
Builds and maintains global equity data pipelines for a quant fund, cleaning and aligning market data from vendors like Bloomberg and Refinitiv to power AI-driven trading strategies.
Optimize and lead the design of high-performance backend systems for ML recommendation models using C/C++, graph optimizations, and model compilation stacks.
Build and deploy AI-driven travel systems: optimize airline networks, automate agency workflows, and enhance retailing using ML, GenAI, and MLOps on GCP.
Analyze geospatial data to support land governance and hydrocarbon operations using ESRI tools, Python, and AI/ML; design dashboards and automate workflows for executive decision-making.
Design, train, and deploy AI/ML models and generative AI solutions using cloud-native platforms like GCP Vertex AI, Azure ML, or AWS SageMaker.
Build and deploy AI models to improve player experience in Kammelna Games, including churn prediction and personalization, using Python, ML frameworks, and MLOps tools.
Build and deploy ML/AI models (regression, classification, deep learning, LLMs) for business use cases, integrate outputs into Power BI dashboards, and productionize solutions for clients.
Build and deploy ML/AI models (forecasting, deep learning, LLM summarization) and integrate insights into Power BI dashboards for data-driven decisions.
Build and deploy ML models to detect anomalies in time-series sensor data for climate/industrial systems using Python, SQL, and MLOps practices.
Build and deploy ML models and deep-learning systems in Python, integrating them into production apps and APIs while collaborating with cross-functional teams.
Designs and deploys computer-vision models (object detection, segmentation) using PyTorch/TensorFlow and OpenCV, optimizing for edge/cloud deployment and managing data pipelines.
Design and deploy AI/ML models (predictive, NLP, computer vision) for enterprise use cases, collaborating with stakeholders to deliver end-to-end analytics solutions on large-scale data.
Build and deploy production-grade AI/ML models and features, focusing on deep learning, MLOps, and end-to-end automation for measurable business impact.
Builds and deploys ML models to optimize marketing spend and forecast demand, using Python, SQL, and basic neural networks with mentorship from HQ’s data-science team.
Data Scientist builds predictive models and dashboards in Python/R with Power BI, working with stakeholders to turn business needs into data-driven insights and solutions.
Build and deploy AI/ML models in Python and Azure for an insurance-focused client, focusing on MLOps pipelines, LLM integration, and executive dashboards.
Build and deploy ML models for predictive maintenance and energy optimization using Python, FastAPI, and Azure ML in ETAP’s electrical digital twin platform.
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