Benevity is hiring a Senior Staff Developer AI and ML in Vancouver!
Benevity, a Canadian B Corporation that builds corporate purpose and social-impact software for many Fortune 100 companies, is hiring a Senior Staff Developer for AI and Machine Learning in Vancouver. This is a newly created position conceived as the technical anchor of the engineering organization's GenAI strategy: the successful candidate will own end-to-end ML architecture and shape how AI capabilities are delivered across the platform. The role sits at the intersection of research and production engineering, requiring both hands-on depth and the strategic judgment to turn ambiguous business problems into reliable, measurable AI products. It is a hybrid position, with no fixed in-office quota but an expectation that employees gather in person for onboarding, projects and team connection when it adds value.
Key responsibilities
- Own the end-to-end machine learning architecture, covering data ingestion, feature stores, model serving and monitoring
- Set the long-term roadmap for AI infrastructure and the orchestration framework
- Build AI capabilities as self-service primitives such as APIs, SDKs and shared patterns so other domain teams can ship AI features independently
- Establish MLOps standards that make the ML ecosystem as testable, maintainable and scalable as core application code
- Architect and evolve LLM-powered products including copilots, search, assistants and agents, with RAG pipelines, tool integrations and multi-step reasoning
- Design evaluation frameworks for GenAI combining offline benchmarks, online metrics and human feedback
- Define guardrails and safety mechanisms addressing prompt injection, hallucination and responsible AI
- Create the golden path for model versioning, A/B testing, drift detection and automated rollback
- Partner with product managers, data scientists and ML engineers to translate business needs into technical requirements
- Lead design reviews and mentor engineers on system design and performance optimization
- Ensure architecture complies with security policies, industry regulation and best practice
Key requirements
- Bachelor's or Master's degree in computer science, mathematics or a related field, or equivalent experience
- 8+ years in software engineering, including 4+ years architecting and running ML models in production at scale
- 2+ years of technical leadership on scalable platform or modernization work
- Prior Staff-level or Senior experience with architecture ownership and mentoring
- Experience building internal self-service platforms for other engineering teams, not only product features
- Deep MLOps expertise spanning training, evaluation, deployment, monitoring and lifecycle management
- Strong AWS or Google Cloud background with distributed AI/ML workloads
- Solid data architecture and engineering knowledge: pipelines, feature engineering, modeling, large-scale processing
- Familiarity with feature stores, experiment tracking, model registries and orchestration frameworks
- Proficiency in Python and frameworks such as TensorFlow, PyTorch or scikit-learn, plus CI/CD for ML
- Hands-on with LLM systems: model selection, latency/cost/quality trade-offs, prompt engineering, RAG, vector databases and agentic orchestration frameworks
- Knowledge of data and model governance, security, privacy, bias and explainability
- Seniority: Senior Staff
- Work mode: Hybrid
- Key skills: Python, TensorFlow, PyTorch, scikit-learn, MLOps, AWS, Google Cloud, RAG, LLM orchestration, LangChain, LlamaIndex, vector databases, prompt engineering, CI/CD, feature stores
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