Top Machine Learning Jobs in Calgary

The Founding Machine Learning Engineer will develop and train models, pipelines, and methodologies for semantic graph systems. Responsibilities include building models for knowledge extraction, evaluating AI data graphs, and fine-tuning LLMs. The role requires significant experience in machine learning, NLP, and expertise with language models and data manipulation tools.

The Founding Engineer will build and scale GPU infrastructure for real-time AI, optimizing inference engines and models for applications like gaming and robotics. This role involves shaping the technical direction and contributing to both architectural roadmap and customer engagement, requiring strong leadership in a fast-paced environment.

As a Senior Machine Learning Engineer at Blackpoint Cyber, you will lead the development of machine learning solutions for AI products, focusing on building and deploying models on cloud infrastructure, implementing ML workflows, and collaborating with various teams to enhance cybersecurity measures.

As a Machine Learning Engineer II, you will create and improve production ML models, design and validate distributed ML platforms, collaborate with teams to deliver insights, and document tools for easier usage by Data Scientists and Engineers.

The Machine Learning Implementation Engineer will collaborate with customer Analytics/BI teams to implement OfferFit's AI decisioning engine, improve product architecture, develop reusable data pipelines, and support customers. The role involves working closely with ML pipeline development and overseeing customer success while following best coding and development practices.

The Staff Software Engineer will design scalable product architectures to enhance machine learning capabilities, solving complex problems with high ambiguity while leading cross-team collaborations and mentoring junior engineers. They will be responsible for high-quality code delivery and contributing to innovative improvements across the engineering organization.

As a Senior Software Engineer II specializing in Machine Learning at Narvar, you'll design, deploy, and optimize machine learning algorithms across various domains, manage large datasets, and contribute to the overall ML operations. You'll also guide the data team, build tools, and frameworks while leveraging your extensive knowledge in software engineering, statistics, and data science.

As a Senior Machine Learning Engineer at Coinbase, you will utilize advanced machine learning methodologies to tackle challenges like fraud detection and improve user experience. Responsibilities include building production-ready ML systems and democratizing ML tools for the company.

The Staff Machine Learning Engineer will lead the development of Generative AI solutions, build training infrastructures for language and vision models, implement testing procedures, and optimize models for performance within the Firefox team.

As a Machine Learning Engineer, you'll develop and enhance AI algorithms for Zoom's AI Companion product, collaborating with cross-functional teams, participating in code reviews, and identifying system improvement opportunities while staying up-to-date with GenAI advancements.

The Senior Machine Learning Engineer will design, develop, and optimize generative AI models for various applications. Responsibilities include model training and fine-tuning, performance evaluation, data preparation, and collaboration with cross-functional teams. The role also involves deploying scalable AI solutions and staying abreast of the latest advancements in machine learning and generative AI.

As a Senior Machine Learning Scientist at McAfee, you'll design and deploy machine learning models for pricing optimization and personalized recommendations. Collaborating across teams, you'll create algorithms to enhance consumer journeys, and analyze experiments to measure the effectiveness of your solutions.

The Senior Backend Engineer (AI/ML) will design and implement REST APIs for AI/ML back-end services, optimizing for scalability and low latency. Responsibilities include collaborating across teams, resolving performance issues, enhancing system reliability, and ensuring secure user data handling.

The Senior Machine Learning Engineer will design, develop, and productionize ML systems, focusing on generative models. Responsibilities include collaborating with research teams, optimizing model training, and advocating engineering best practices, while working with cutting-edge technologies in a high-performance environment.

As a Machine Learning Engineer on the GenAI Engineering team, you will develop and enhance AI algorithms for the AI Companion product, collaborate with cross-functional teams, participate in code reviews, and integrate research findings into scalable solutions, while staying updated on GenAI advancements.

The Senior MLOps Engineer will ensure the operational efficiency of Autodesk's AI/ML Platform by optimizing MLOps practices, implementing automated deployment, and maintaining scalable infrastructure. Responsibilities include monitoring model performance, enforcing security compliance, and collaborating with data engineers to enhance the AI/ML lifecycle. This role requires a strong background in DevOps, cloud platforms, and machine learning frameworks.

Develop and architect systems and data pipelines that enhance machine learning lifecycle at Pinterest, collaborate with signal owners and teams to optimize signal delivery, and support scalable backend service development.