Top Machine Learning Jobs in Vancouver

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

The Machine Learning Architect will design ML systems, mentor teammates, and work with AWS to deliver solutions, ensuring alignment with customer needs and technical requirements.

As a Machine Learning & Game Tech Architect, you'll design and integrate AI into gaming systems, oversee ML applications, and maintain quality standards, while collaborating with teams to enhance functionality and innovation.

Design and lead end-to-end AI/ML and GenAI architectures (data pipelines, training, inference, MLOps). Advise clients, integrate LLMs, build RAG systems, benchmark platforms, mentor teams, ensure responsible AI, and align ML strategy with business goals.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

Join Apera AI as a Senior Machine Learning and Computer Vision Applied Scientist, leading projects in object detection, model integration, and real-time deployment in robotics.

The Machine Learning Engineer will design and build core ML systems for AI agents, managing their lifecycle, from design to deployment, and ensuring scalability and reliability.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

The role involves solving customer problems by building ML solutions, engaging with various stakeholders, and taking ownership of the outcome through deployment.

The role involves designing AI models and training methods leveraging wafer-scale hardware and collaborating with various teams and partners in AI and computational science.

The R&D Engineer will design and implement performance workloads on Cerebras' wafer-scale hardware, collaborating across teams to advance AI and scientific computing. Responsibilities include optimizing performance models, contributing to the technology roadmap, and publishing research findings.

As a Machine Learning Engineer, you will develop user experiences using LLMs and predictive analysis, deliver ML solutions, and ensure continuous improvement in AI products at scale.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

The role involves designing and implementing MLOps pipelines, optimizing machine learning processes, and ensuring model performance and compliance in a collaborative environment.

As a Principal Software Engineer II, you will build and maintain machine learning components for Elasticsearch, optimizing model performance and collaborating with various engineering teams on advanced analytics.

The ML Infrastructure Engineer will build and maintain ML systems, manage production workflows, automate deployments, and support data scientists with scalable infrastructure.

Lead technical direction and execution of CX automation systems to reduce support costs and speed resolution. Architect scalable backend services, decision engines, and workflows that take real actions with fraud/abuse guardrails. Partner with Product and CX Operations, drive platform investments, and measure automation effectiveness.

Lead design and deployment of production-grade AI solutions, build multi-agent systems and cloud-native ML infrastructure, apply rigorous statistical evaluation, implement generative and predictive models, champion MLOps and data pipeline best practices, and collaborate with clients to translate business needs into technical solutions.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

Design and build agentic AI workflows for biological and clinical data curation and analysis. Implement context engineering (RAG variants), prompt and agent architecture optimization, LLM tool-use integrations, and evaluation benchmarks. Collaborate with bioinformatics and clinical experts to translate domain problems into reliable, production-quality agentic systems.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.