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Designs and evaluates scalable machine learning architectures for a large U.S. bank, guiding adoption of cloud-based ML platforms and MLOps practices to enable predictive modeling and AI-driven financial solutions.
Designs and leads agentic AI platforms for NVIDIA Marketing, translating marketing needs into scalable AI agents for personalization, recommendations, and workflow automation using LLMs, RAG, and enterprise integrations.
Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and…
Job Description Summary #LI-Hybrid This position plays a vital role in integrating AI-driven solutions across various platforms, fostering collaboration between the US commercial team and the India-based data science…
The Senior Data Scientist will design and deploy end-to-end decision science systems, including forecasting, recommendation engines, and optimization models, within a hybrid-remote environment in Toronto. The role involves working with Python, PyTorch, and TensorFlow to build production-grade data products for the lottery and gaming industry.
Data Scientist – Job Description (10+ Years Experience) Job Title: Data Scientist Experience Level: 10+ years of relevant experience in Data Science, Machine Learning, and Advanced Analytics Location: Canada Role…
For Canada Applicants: This posting is for an existing vacancy. the company utilizes AI tools to assist in assessing candidates in our hiring processes. Note: By applying to this position you will have an opportunity…
Senior Software Engineer building and scaling Kubbly's AI agent platform for business messaging, owning architecture, CI/CD pipelines, cloud infrastructure (AWS), and backend integrations.
Design and build AI-powered web applications by developing ML models with PyTorch and integrating them into production systems via Python (FastAPI/Flask) or Java (Spring Boot) backends, with deployment on cloud or on-premise infrastructure.
Senior Backend Engineer developing and maintaining Shopee's e-commerce search user-end products, focusing on backend architecture, performance, and search experience. Requires experience in personalized recommendation or search systems, data structures, algorithms, and Linux-based development.
Build and optimize distributed ML training/inference systems for ByteDance’s AI platforms, focusing on scheduling, resource allocation, and model deployment across heterogeneous hardware.
Research Scientist at ByteDance working on ultra-large-scale multimodal recommendation systems, focusing on distributed ML infrastructure, model training/inference optimization, and algorithm-engineering co-design for products like TikTok.
Senior Data Scientist building and evaluating ML models (regression, classification, forecasting) using SQL and Python, delivering end-to-end data science solutions for TCS's AI CoE in Toronto.
Senior Data Scientist supporting TCS's AI CoE with end-to-end data science solutions—building and evaluating regression/classification models using SQL and Python, with exposure to Azure, Databricks, and MLflow in Toronto.
Builds scalable real-time recommendation systems and distributed data infrastructure, integrating cloud services and AI/ML models to analyze user behavior and optimize software performance.
Backend Engineer designing and scaling backend infrastructure for AI recommendation systems at a fintech company, using Kubernetes, Docker, Ray Serve, and ML serving platforms.
Designs and builds AI/ML-powered features, models, and APIs to enhance customer products; collaborates with product and data teams to deploy scalable, high-performance AI solutions.
Build and maintain full-stack marketplace features and ML Ops infrastructure to match renters with homes, using Ruby/JavaScript/Go/Python and tools like Vertex AI and Chalk.
The Director of Data Science will lead a team to develop predictive models and customer intelligence strategies for media brands, focusing on personalization, engagement, and product growth. The role involves leveraging Python, SQL, and machine learning to drive actionable insights across web and mobile platforms.
ML Engineer taking models from development to production—forecasting, ranking, and recommendation systems—on a Databricks-based data platform, using Python, SQL, and cloud services.
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