Top Python Jobs in Toronto

Optimize, compress, and distill large language and vision models for on-device inference. Build pipelines for distillation and hardware-specific compilation, and benchmark performance across NPU/GPU architectures.

Design, orchestrate, and optimize large-scale LLM pre-training across 1,000+ GPUs. Implement 3D parallelism, manage GPU clusters (SLURM/Kubernetes), optimize InfiniBand/RDMA networking and memory, and automate checkpointing and failure recovery for long training runs.

Design and build the Neki control plane to provision, scale, and heal sharded PostgreSQL clusters. Implement high-availability, disaster recovery, backup/restore, and migration tooling. Operate distributed, fault-tolerant services on Kubernetes, participate in on-call rotations, and work with customers to translate workloads into platform improvements.

Research and build efficient ML systems for large-scale LLMs and agentic RL: design algorithms and system techniques, prototype in training/inference stacks, run large-scale experiments, and translate findings into production or publications.

Design, build, and operate end-to-end training and inference infrastructure for large language and multimodal models. Improve efficiency (memory, parallelism, kernel optimizations), ensure robust scalable training and RL pipelines, optimize low-latency/high-throughput serving (quantization, caching, speculative decoding), manage multi-GPU and multi-cloud orchestration, and productionize new algorithms with strong observability and reproducibility.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

You will design and implement IAM systems, own authentication and authorization, and ensure secure-by-default principles across Hadrian's API platform.

The role involves developing, adapting, and implementing machine learning algorithms for computer vision tasks in power grid analysis. Responsibilities include experimentation, error analysis, and project ownership.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

Perform technical security assessments, embed security into development pipelines, run vulnerability scanning and penetration tests, develop incident response plans and playbooks, lead incident response, monitor alerts, and train teams on security practices while collaborating with development and operations.

The Director of Epidemiology Pipeline collaborates on virology clinical trials, providing scientific expertise, leading project proposals, and overseeing study management and regulatory compliance.

As a Power Supply Design Engineer, you will design and verify power solutions for digital electronics, manage vendor relationships, and provide expertise on complex circuits. You will be involved in high-visibility projects that influence product strategy.

As a Senior SDET, you will enhance testing practices, improve CI pipelines, mentor engineers, and ensure platform reliability through comprehensive testing strategies.

Research AI threats, analyze threat actor behavior, produce actionable intelligence, collaborate with teams, and publish findings in the cybersecurity domain.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Design and execute automated system- and solution-level tests (Python) for optical pluggable products, collaborate with cross-functional teams in Agile, maintain test scripts in Git, report test execution and defects, and drive continuous QA improvements and compatibility testing with third-party equipment.

Design complex multilayer PCBs, manage the design process from concept to production, verify hardware, and resolve customer issues.

Responsible for managing wafer level testing processes to improve yield, overseeing test equipment, and coordinating with external suppliers and engineering teams.

Lead end-to-end delivery of large-scale analytics and data management programs: enforce delivery best practices, manage multi-workstream teams, liaise with senior stakeholders, ensure quality/performance on cloud data platforms, and drive account growth and talent development.

Lead the Treasury team to develop and maintain backend services ensuring reliability in financial transactions, while implementing features and improving systems.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

Build and operate secure, scalable ML pipelines and hybrid GPU infrastructure for training, fine-tuning, serving, and governing open-source LLMs and agentic apps. Implement CI/CD, model versioning, observability, benchmarking, security controls, and integration with RAG/agent tools and vector DBs to support production deployments across tenants.

Design, train, evaluate, and optimize agent-native LLMs and RAG pipelines for enterprise use. Build training and RL pipelines (RLHF/DPO/PPO), embedding-based memory, evaluation harnesses, observability, and inference optimization across cloud and on-prem environments.

Founding full-stack engineer to architect and build a production platform combining large-scale data systems and AI-native agents. Work across backend, frontend, data pipelines, agents, and deployment systems; define architecture, devops, CI/CD, and early engineering processes while shipping features and growing the team.