Top Machine Learning Jobs in Vancouver

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

Develop and propose enhancements to graphics API specifications (Vulkan, OpenGL, WebGL/WebGPU, SPIR-V, glTF), apply computer graphics and GPU computing techniques, engage in KHRONOS/W3C standard activities, and contribute ML and parallel computing expertise with a strong publication record.

Build and deploy NLP and generative AI solutions using transformer-based and other ML models. Develop LLM-based features, preprocess complex unstructured data, collaborate with engineering, product, and MLOps teams, and iterate in an agile, cross-functional environment to improve customer workflows and efficiencies.

Develop and deliver production-ready machine learning and computer vision solutions for mining operations, owning projects from research through deployment. Work across edge, embedded and cloud environments, collaborate with multidisciplinary teams, mentor developers, contribute to documentation and governance, and monitor model performance to improve safety, efficiency and sustainability at scale.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

As a Principal AI Researcher, you will lead advanced AI research in agentic systems and LLMs, shaping research direction, collaborating with engineering teams, and publishing in top-tier venues while fostering a culture of scientific rigor.

The role involves leading AI/ML technical planning, evaluating new technologies, collaborating with stakeholders, and fostering innovation in the team.

Lead research, design, and implementation of large-scale cloud data ingestion, preprocessing, distributed training, and benchmarking for geospatial foundation models focused on agriculture. Contribute to model architecture, fine-tuning, tooling, documentation, and Agile development processes.

Provide embedded legal counsel to product and engineering on privacy, IP, and consumer protection; lead Arena's global privacy program (GDPR, CCPA/CPRA, cross-border transfers); advise on AI governance and responsible deployment; support commercial contracts and data flow frameworks; build privacy processes, playbooks, internal agents, and legal-tech integrations to scale operations.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

As a Research Engineer, you will develop and enhance AI algorithms for self-driving vehicles, collaborating with scientists to advance technology and support deployment in production systems.

Manage and grow strategic partnerships across US & Canada for a Google Cloud-focused AI and data consultancy. Drive co-sell initiatives, GTM planning, partner enablement, joint marketing, event execution, partner onboarding, and pipeline generation while tracking partner performance and reporting impact.

Lead design, development, and integration of AI/ML features into FortiAnalyzer for security analytics, anomaly detection, and automated response. Manage software developers and data scientists, oversee full ML pipeline (data, training, deployment, optimization), ensure production scalability and security, and collaborate with product, security, and engineering teams.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

As a Senior Machine Learning Engineer, you'll design and develop AI systems, focusing on LLMs and improving agent performance while mentoring engineers.

Design, build, and operate scalable backend services in Python or Go to power underwriting decisioning. Integrate statistical and ML models, implement APIs (REST, gRPC/GraphQL), ensure observability and testing, lead projects, and collaborate with product, data science, and underwriting teams to automate underwriting workflows.

Develop, train, deploy, and optimize machine learning models for research and production ultrasound applications. Build scalable ML data pipelines and tools, automate retraining, evaluation, and monitoring, and improve inference speed, robustness, and maintainability. Collaborate with researchers and software engineers to productionize ML research while reducing technical debt and communicating concepts to technical audiences.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

Build and deploy applied machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets. Develop feature pipelines, training datasets, evaluation frameworks, confidence scoring, and production inference services. Collaborate with engineering, research, security, and product teams to transform raw Internet telemetry into high-quality datasets and customer-facing insights.

Industry Expert who reviews and defends advanced AI, ML, distributed systems, and forward-deployed engineering projects. Responsibilities include challenging architecture decisions, chairing mock review boards and executive presentations, hosting one or two technical sessions monthly, and serving as the escalation point for instructors. The role requires production-scale engineering judgment, strong technical communication, and expertise in agentic systems, LLM evaluation, infrastructure, observability, model serving, RAG, or enterprise deployments.

Develop and optimize auto-labelling systems using ML and computer vision, manage data pipelines, and collaborate with researchers.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

The Director of Engineering will lead and scale Buzz Solutions' engineering organization, focusing on AI, infrastructure, and platform systems while ensuring best practices and high-quality solutions.