Benevity
Staff Developer - AI/ML
Toronto, Ontario · Staff+
Sponsorship not specifiedDetected 28 days ago
PythonJavaPHPVue.jsDistributed SystemsGitVector DatabasesAWSGCPAzureCloud PlatformsCI/CDMachine LearningTensorFlowPyTorchscikit-learnData EngineeringLLMsRAGMLOpsAI OrchestrationA/B TestingTest AutomationResearch
About the role
- MEET BENEVITY Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about.
- We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more!
Responsibilities
- Design and oversee the development of robust end-to-end ML architecture, from data ingestion and feature stores to model serving and monitoring.
- Oversee the design, implementation, and maintenance of our AI/ML ecosystem.
- Act as a force multiplier for the team by conducting high-level design reviews and mentoring engineers on system design and performance optimization.
- Design and implement robust evaluation frameworks for GenAI systems, incorporating offline benchmarks, online metrics, and human-in-the-loop feedback.
- Drive best practices for prompt engineering, agent design, and orchestration frameworks, ensuring maintainability and performance at scale.
- Identify opportunities for process improvements and implement solutions to enhance platform performance and efficiency.
- Familiarity with LLM-based systems and GenAI applications, including systems design, evaluation strategies, and observability for non-deterministic systems.
- Experience building agentic workflows, including multi-step reasoning, tool use, and orchestration frameworks (e.g., LangChain, LlamaIndex, ADK, or custom frameworks).
Requirements
- Bachelor's or Master's degree in Computer Science, Mathematics, or a related field, or equivalent deep professional experience.
- 7+ years of software engineering experience, with at least 4+ years architecting and deploying ML models in production at scale.
- Proven experience operating at a Staff or Senior level, including technical leadership, architecture ownership, and mentoring engineers.
- Deep expertise in MLOps and production ML systems, including model training, evaluation, deployment, monitoring, and lifecycle management.
- Strong experience with cloud platforms (AWS, Azure, or Google Cloud), including designing and operating scalable, distributed AI/ML workloads.
- Experience with ML infrastructure and tooling, such as feature stores, experiment tracking, model registries, and orchestration frameworks.
- Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), with strong software engineering fundamentals.
- Experience with CI/CD and ML deployment pipelines, including automated testing, validation, and rollback strategies for ML systems.
- Strong understanding of LLM architectures and trade-offs, including model selection, latency, cost, and quality optimization.
- Experience designing and implementing RAG (Retrieval-Augmented Generation) systems, including embedding strategies, vector databases, and retrieval optimization.
Skills
- Benevity's software architecture has evolved to include a diverse technology stack.
Benefits
- Experience with prompt engineering and prompt orchestration, including techniques like few-shot learning, chain-of-thought, and tool/function calling.
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This listing is sourced directly from Benevity's careers page and normalized into a canonical job model.