Top Machine Learning Jobs in Ottawa

Responsible for developing and deploying AI/ML models, integrating systems, optimizing LLM performance, and implementing MLOps practices within GCP.

The Director of Engineering, AI will lead AI initiatives, drive product strategy, manage engineering teams, and ensure effective technical execution in a fast-paced environment.

The Senior Software Engineer II, Machine Learning will design and deploy ML algorithms, work with consumer data, and lead data teams.

As a Machine Learning Intern at Ema, you will work on building and deploying machine learning models, analyzing datasets, and collaborating with senior engineers in a fast-paced startup environment.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The ML Solutions Architect will lead technical discussions, design ML architectures, and ensure client satisfaction through effective communication and deep technical expertise in ML solutions.

The ML Tech Lead will provide technical leadership, mentor engineers, guide technical decisions, and contribute to complex ML projects and architecture.

As a Senior ML Engineer, you'll design and deploy ML solutions, mentor junior engineers, and enhance ML practices and infrastructure.

Senior consultant who designs, implements, and deploys generative AI solutions (LLMs/agents) in cloud and on-prem environments, works directly with clients, writes production-quality code, and supports proposals and sales.

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

The role involves designing, developing, and deploying machine learning models on GCP while ensuring reliability, performance, and scalability of AI applications.

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.

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

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

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.

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.

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.

As a Senior Machine Learning Engineer specializing in Reinforcement Learning, you will develop and deploy RL solutions, optimize ML models, and lead client discussions while ensuring high-quality engineering practices are followed.

The Principal AI Engineer at OutSystems will lead the development of AI systems, collaborate cross-functionally, and mentor other AI engineers in building and deploying scalable AI solutions.

Design, develop, and deploy production-grade ML and GenAI solutions; build scalable pipelines and infrastructure; optimize models; mentor engineers; conduct experiments, code reviews, and contribute ML best practices and accelerators.