recruiting the next in tech
Toronto, Ontario
TekRek was founded on the simple vision of making recruitment as efficient as possible. Recruitment is one of the most important undertakings in building a successful business and we at TekRek understand this. That is why we believe in combining a data driven recruiting process with a human touch to engage and interact with the best candidates in the Technology space. Youtube: https://www.youtube.com/@tekrek/videos Meetup: https://www.meetup.com/tekrek-speaker-series/ TekRek's core areas of recruitment are Software Development and Data. Key roles include: - Director/Head of IT/CIO/CTO - Front-end Developer (ReactJS, AngularJS, HTML) - Back-end Developer (NodeJS, Java, C#, PHP, Python, RoR) - DevOps/Site Reliability (AWS Cloud, Micro-services) - Mobile Developer (iOS, Android) - Cloud Engineer (AWS, Azure, GCP) - CDO, SVP, VP, Director Data - Head of Data Science - Senior Data Scientist - Senior Machine Learning Engineer - Analytics Manager - Senior Data Engineer - Data Architect - Analytics Engineer - Data Analyst
On-site
Onboard data sources to the bank’s central platform by identifying source owners, configuring mappings and connectors, and establishing reliable load processes. Develop Python automation for deployments, data loads, trade reprocessing, reconciliation, alerting, and health checks, while coordinating business, platform, and support teams.
On-site · Toronto
Build and maintain Databricks lakehouse pipelines, data models, and architecture across multiple client engagements, turning disconnected data into useful dashboards and analysis. Support machine learning deployment and data governance, present recommendations to executive stakeholders, and prototype tools for future client work.
Hybrid · Toronto
Build and deliver full-stack product features across Python services, APIs, background jobs, and React/TypeScript interfaces, from requirements and design through testing, release, and production support. Use AI coding agents responsibly, and improve PostgreSQL performance, tests, documentation, CI/CD, and repository context.
Hybrid · Toronto
Develop and evolve a large-scale integration platform, build new integrations, and design reliable APIs for customers. Shape technical strategy, improve testing and observability, optimize distributed systems, and collaborate directly with customers on features and product launches.
On-site · Toronto
Own the development of platform capabilities for data replication, storage, enrichment, reporting, and scalable streaming and batch pipelines. Design petabyte-scale storage and real-time ingestion systems, and implement data lineage, distributed tracing, and observability.
Hybrid · Toronto
Build and support Android applications for point-of-sale terminals, integrating payment and peripheral hardware while ensuring secure, stable, responsive workflows. Design Azure services and APIs for device monitoring and fleet management, and develop data pipelines that turn device and transaction telemetry into monitoring, alerts, and reports.
Hybrid · Toronto
Review requirements and acceptance criteria, design functional and regression coverage, and build and maintain UI, API, and end-to-end automation. Test REST APIs and back-end transactional data, run automated suites in Azure DevOps pipelines, and communicate failures clearly to engineering.
Remote · Canada
Set the technical vision and architecture for the clinical platform while remaining hands-on in production code and delivery. Build secure, scalable AI infrastructure and establish engineering practices, hiring standards, and team culture in partnership with company and clinical leadership.
On-site · Vancouver
Lead the design, architecture, and delivery of customer-facing enterprise products, spanning React interfaces, Python services, and data stores, while owning their security, scalability, and long-term health. Set the product area's technical roadmap, document architectural plans, hire and mentor engineers, and partner with product and customer-facing teams to deliver measurable outcomes.
Hybrid · Montréal
Build, train, evaluate, and deploy machine learning and deep learning models, including foundation-model fine-tuning and RAG systems, for client projects across industries. Establish and maintain production MLOps workflows, and collaborate with clients and internal teams to scope business problems and deliver scalable, reliable solutions.
On-site
Design, build, and deploy production generative AI solutions on Vertex AI, including evaluation frameworks, human review processes, monitoring, and safe rollback paths. Own live solutions operationally and work directly with business users to integrate AI with legacy systems and automations, test releases end to end, and confirm they meet business needs.
Hybrid · Montréal
Design and deliver scalable client data platforms from initial scoping and architecture through production, including high-volume batch and streaming pipelines for AI and machine learning workloads. Advise client stakeholders on technical roadmaps and architecture trade-offs, while ensuring data quality, reliability, monitoring, and effective data modeling.
On-site · Vancouver
Lead two engineering teams focused on agentic workflows and natural language product experiences. Drive the multi-quarter roadmap while building processes and standards to scale the engineering organization.
On-site · Toronto
You will analyze AI and LLM consumption to optimize token usage and implement cost-effective model routing logic. Additionally, you will develop frameworks for usage tracking, cost attribution, and FinOps controls across business entities.
Remote · Canada
Partner with customers to translate operational workflows into reliable AI-powered processes and lead deployments from implementation to production. Collaborate with product and engineering teams to refine AI agents and improve overall deployment outcomes.
