Top Machine Learning Jobs in Toronto

As a Compiler Engineer at Cerebras Systems, you will design and optimize compiler technologies for AI chips using LLVM and MLIR frameworks. You will work closely with the machine learning team to enhance compiler performance, address bottlenecks, and ensure efficient resource utilization for AI applications.

The ML Software Tool Development Engineer is responsible for designing and expanding build tools for new hardware and software, resolving issues for ML applications, and collaborating with cross-functional teams to enhance solutions. Candidates should have skills in hardware debugging, CAD tool design, and UI/UX data visualization, with a strong knowledge of C++ and Python.

The Staff Machine Learning Engineer at Altos Labs will design and optimize large-scale machine learning systems, collaborating closely with computational scientists across various disciplines. Responsibilities include building data transformation pipelines, managing model serving, and mentoring software engineers while promoting effective software engineering practices.

The Machine Learning Engineer will work on improving query understanding, optimize machine learning algorithms, and collaborate with cross-functional teams to deliver effective product solutions for user queries.

As a Software Engineer in AI Decisioning at Hightouch, you will design and build scalable backend systems and machine learning infrastructure for real-time data analysis. Collaborating closely with product teams, you will develop AI-driven features that automate decision-making and enable hyper-personalization for growth teams, shaping the future of marketing operations.

As a Senior Software Development Engineer, you'll collaborate with machine learning engineers to create and deploy scalable machine learning solutions. Your responsibilities include building ETL pipelines, secure web services, multitenant architectures, and interactive prototypes, while ensuring code quality and collaborating across teams to deliver impactful features.

The Sr. Machine Learning Engineer will develop ML-powered information retrieval and recommendation services at Workday, utilizing advanced LLMs, knowledge graphs, and predictive analysis. Responsibilities include building production ML models, developing APIs/microservices, collaborating with engineers to enhance Workday's offerings, and continually refining ML solutions through research and application of recent advancements in NLP.

The Sr. Machine Learning Engineer will develop ML-powered information retrieval and recommendation services, utilizing advanced models and techniques while collaborating with engineers to enhance user interactions. Responsibilities include designing ML models, deploying APIs, and improving product performance using large datasets.